B.

Sc- Information Technology Syllabus under CBCS Pattern with effect from 2023-2024 onwards

PERIYAR UNIVERSITY
PERIYAR PALKALAI NAGAR
SALEM-636011

DEGREE OF BACHELOR OF SCIENCE

Syllabus for

B.Sc., INFORMATION TECHNOLOGY

(SEMESTER PATTERN- CBCS)

(For Candidates admitted in the colleges affiliated to

Periyar university from 2023-2024 onwards)

 1. Introduction

B.Sc. Information Technology

Education is the key to development of any society. Role of higher education is crucial for
securing right kind of employment and also to pursue further studies in best available world class
institutes elsewhere within and outside India. Quality education in general and higher education in
particular deserves high priority to enable the young and future generation of students to acquire
skill, training and knowledge in order to enhance their thinking, creativity, comprehension and
application abilities and prepare them to compete, succeed and excel globally. Learning Outcomes-
based Curriculum Framework (LOCF) which makes it student-centric, interactive and outcome-
oriented with well-defined aims, objectives and goals to achieve. LOCF also aims at ensuring
uniform education standard and content delivery across the state which will help the students to
ensure similar quality of education irrespective of the institute and location.

Computer Science is the study of quantity, structure, space and change, focusing on problem
solving, application development with wider scope of application in science, engineering,
technology, social sciences etc. throughout the world in last couple of decades and it has carved out
a space for itself like any other disciplines of basic science and engineering. Computer science is a
discipline that spans theory and practice and it requires thinking both in abstract terms and in
concrete terms. Nowadays, practically everyone is a computer user, and many people are even
computer programmers. Computer Science can be seen on a higher level, as a science of problem
solving and problem solving requires precision, creativity, and careful reasoning. The ever-evolving
discipline of computer science also has strong connections to other disciplines. Many problems in
science, engineering, health care, business, and other areas can be solved effectively with computers,
but finding a solution requires both computer science expertise and knowledge of the particular
application domain. Computer science has a wide range of specialties. These include Computer
Architecture, Software Systems, Graphics, Artificial Intelligence, Computational Science, and
Software Engineering. Drawing from a common core of computer science knowledge, each specialty
area focuses on specific challenges. Computer Science is practiced by mathematicians, scientists and
engineers. Mathematics, the origins of Computer Science, provides reason and logic. Science
provides the methodology for learning and refinement. Engineering provides the techniques for
building hardware and software.
The Students completing this programme will be able to present Software application clearly
and precisely, make abstract ideas precise by formulating them in the Computer languages.
Completion of this programme will also enable the learners to join teaching profession, enhance
their employability for government jobs, jobs in software industry, banking, insurance and
investment sectors, data analyst jobs and jobs in various other public and private enterprises.

LEARNING OUTCOMES-BASED CURRICULUM FRAMEWORK GUIDELINES BASED

REGULATIONS FOR UNDER GRADUATE PROGRAMME
Programme: B.Sc., Information Technology

Programme Code:

Duration: 3 years [UG]

Programme PO1: Disciplinary knowledge: Capable of demonstrating comprehensive
Outcomes: knowledge and understanding of one or more disciplines that form a part of
an undergraduate Programme of study
PO2: Communication Skills: Ability to express thoughts and ideas effectively
in writing and orally; Communicate with others using appropriate media;
confidently share one‘s views and express herself/himself; demonstrate the
ability to listen carefully, read and write analytically, and present complex
information in a clear and concise manner to different groups.
PO3: Critical thinking: Capability to apply analytic thought to a body of
knowledge; analyse and evaluate evidence, arguments, claims, beliefs on
the basis of empirical evidence; identify relevant assumptions or
implications; formulate coherent arguments; critically evaluate practices,
policies and theories by following scientific approach to knowledge
development.
PO4: Problem solving: Capacity to extrapolate from what one has learned
and apply their competencies to solve different kinds of non-familiar
problems, rather than replicate curriculum content knowledge; and apply
one‘s learning to real life situations.
PO5: Analytical reasoning: Ability to evaluate the reliability and relevance of
evidence; identify logical flaws and holes in the arguments of others;
analyze and synthesize data from a variety of sources; draw valid
conclusions and support them with evidence and examples, and addressing
opposing viewpoints.
PO6: Research-related skills: A sense of inquiry and capability for asking
relevant/appropriate questions, problem arising, synthesising and
articulating; Ability to recognise cause-and-effect relationships, define
problems, formulate hypotheses, test hypotheses, analyse, interpret and
draw conclusions from data, establish hypotheses, predict cause-and-effect
relationships; ability to plan, execute and report the results of an experiment
or investigation
PO7: Cooperation/Team work: Ability to work effectively and respectfully
 with diverse teams; facilitate cooperative or coordinated effort on the part
of a group, and act together as a group or a team in the interests of a
common cause and work efficiently as a member of a team

PO8: Scientific reasoning: Ability to analyse, interpret and draw conclusions

from quantitative/qualitative data; and critically evaluate ideas, evidence and
experiences from an open-minded and reasoned perspective.
PO9: Reflective thinking: Critical sensibility to lived experiences, with self
awareness and reflexivity of both self and society.
PO10 Information/digital literacy: Capability to use ICT in a variety of
learning situations, demonstrate ability to access, evaluate, and use a variety of
relevant information sources; and use appropriate software for analysis of data.
PO 11 Self-directed learning: Ability to work independently, identify
appropriate resources required for a project, and manage a project through to
completion.
PO 12 Multicultural competence: Possess knowledge of the values and
beliefs of multiple cultures and a global perspective; and capability to
effectively engage in a multicultural society and interact respectfully with
diverse groups.
PO 13: Moral and ethical awareness/reasoning: Ability to embrace
moral/ethical values in conducting one‘s life, formulate a position/argument
about an ethical issue from multiple perspectives, and use ethical practices in
all work. Capable of demon starting the ability to identify ethical issues related
to one‟s work, avoid unethical behaviour such as fabrication, falsification or
misrepresentation of data or committing plagiarism, not adhering to intellectual
property rights; appreciating environmental and sustainability issues; and
adopting objective, unbiased and truthful actions in all aspects of work.
PO 14: Leadership readiness/qualities: Capability for mapping out the tasks
of a team or an organization, and setting direction, formulating an inspiring
vision, building a team who can help achieve the vision, motivating and
inspiring team members to engage with that vision, and using management
skills to guide people to the right destination, in a smooth and efficient way.
PO 15: Lifelong learning: Ability to acquire knowledge and skills, including
„learning how to learn‟, that are necessary for participating in learning
activities throughout life, through self-paced and self-directed learning aimed at
personal development, meeting economic, social and cultural objectives, and
adapting to changing trades and demands of work place through
knowledge/skill development/reskilling.
Programme PSO1: To enable students to apply basic microeconomic, macroeconomic and
Specific monetary concepts and theories in real life and decision making.
Outcomes: PSO 2: To sensitize students to various economic issues related to
Development, Growth, International Economics, Sustainable Development and
Environment.
 PSO 3: To familiarize students to the concepts and theories related to Finance,
Investments and Modern Marketing.
PSO 4: Evaluate various social and economic problems in the society and
develop answer to the problems as global citizens.
PSO 5: Enhance skills of analytical and critical thinking to analyze
effectiveness of economic policies.

PO 1 PO2 PO3 PO4 PO5 PO6 PO7 PO8

PSO 1 Y Y Y Y Y Y Y Y
PSO 2 Y Y Y Y Y Y Y Y
PSO3 Y Y Y Y Y Y Y Y
PSO 4 Y Y Y Y Y Y Y Y
PSO 5 Y Y Y Y Y Y Y Y

3 – Strong, 2- Medium, 1- Low

Highlights of the Revamped Curriculum:

 Student-centric, meeting the demands of industry & society, incorporating industrial

components, hands-on training, skill enhancement modules, industrial project, project with
viva-voce, exposure to entrepreneurial skills, training for competitive examinations,
sustaining the quality of the core components and incorporating application oriented content
wherever required.
 The Core subjects include latest developments in the education and scientific front,
advanced programming packages allied with the discipline topics, practical training,
devising mathematical models and algorithms for providing solutions to industry / real life
situations. The curriculum also facilitates peer learning with advanced mathematical topics
in the final semester, catering to the needs of stakeholders with research aptitude.
 The General Studies and Mathematics based problem solving skills are included as
mandatory components in the ‗Training for Competitive Examinations‘ course at the final
semester, a first of its kind.
 The curriculum is designed so as to strengthen the Industry-Academia interface and provide
more job opportunities for the students.
 The Industrial Statistics course is newly introduced in the fourth semester, to expose the
students to real life problems and train the students on designing a mathematical model to
provide solutions to the industrial problems.
 The Internship during the second year vacation will help the students gain valuable work
experience, that connects classroom knowledge to real world experience and to narrow
down and focus on the career path.
 Project with viva-voce component in the fifth semester enables the student, application of
conceptual knowledge to practical situations. The state of art technologies in conducting a
Explain in a scientific and systematic way and arriving at a precise solution is ensured. Such
innovative provisions of the industrial training, project and internships will give students an
edge over the counterparts in the job market.
 State-of Art techniques from the streams of multi-disciplinary, cross disciplinary and inter
disciplinary nature are incorporated as Elective courses, covering conventional topics to the
latest - Artificial Intelligence.
Value additions in the Revamped Curriculum:

Semester Newly introduced Components Outcome / Benefits

Foundation Course  Instill confidenceamong
To ease the transition of learning students
from higher secondary to higher  Create interest for thesubject
education, providing an overview
I of the pedagogy of learning
Literature and analysing the
world through the literary lens
gives rise to a new perspective.
Skill Enhancement papers  Industry readygraduates
(Discipline centric / Generic /  Skilled human resource
Entrepreneurial)  Students are equippedwith essential
skills to
make them employable

 Training on language and

I, II, III, communication skills enable the
IV students gain
knowledge and
exposure in the competitive world.

 Discipline centric skill will improve

the Technical knowhow of solving
real life
problems.

 Strengthening thedomain
knowledge
 Introducing thestakeholders
to theState-of Art
techniquesfrom the streams ofmulti-
disciplinary, cross disciplinary and
inter disciplinary nature
III, IV, V  Emerging topics inhigher
Elective papers
& VI education/industry/ communication
network / health sectoretc. are
introduced with
hands-on-training.
  Exposure to industry moulds students
into solution providers
IV Elective Papers  Generates Industryready graduates
 Employment opportunities enhanced
 Self-learning isenhanced
V  Application of the concept to real
Elective papers situationis conceived resulting
Semester
in tangible outcome

 Enriches the studybeyond the

course.
VI
Elective papers  Developing a researchframework and
Semester
presenting their independent and
intellectual ideas effectively.

Extra Credits:  To cater to the needs ofpeer learners /

For Advanced Learners / Honors degree research
aspirants
Skills acquired from the Courses Knowledge, Problem Solving, Analytical
ability, Professional Competency, Professional
Communication and Transferrable Skill
 Credit Distribution for UG Programmes

Credit

Credit

Credit

Credit

Credit

Credit
Hours

Hours

Hours

Hours

Hours

Hours
Sem I Sem II Sem III Sem IV Sem V Sem VI

Part 1. Part..1. Part..1. Part..1. 5.1 Core 6.1 Core

Language – 3 6 Language – 3 6 Language – 3 6 Language – 3 6 Course – 4 5 Course – 4 6
Tamil Tamil Tamil Tamil \CC IX CC XIII

5.2 Core 6.2 Core

Part.2 Part..2 Part..2 Part..2
3 6 3 6 3 6 3 6 Course – 4 5 Course – 4 6
English English English English
CC X CC XIV

4.3 Core
Course –
1.3 Core 2..3 Core 3.3 Core 5. 3.Core 6.3 Core
CC VII
Course – 5 5 Course – CC 5 5 Course – CC 5 5 5 5 Course 4 5 Course – 4 6
Core
CC I III V CC -XI CC XV
Industry
Module
5. 4.Core
Course –/ 6.4 Elective -
1.4 Core 2.4 Core 3.4 Core 4.4 Core
Project VII Generic/
Course – 5 5 Course – CC 5 5 Course – CC 5 5 Course – 5 5 4 5 3 5
with viva- Discipline
CC II IV VI CC VIII
voce Specific
CC -XII

1.5 5.5
2.5 Elective 3.5 Elective 4.5 Elective 6.5 Elective VIII
Elective I Elective V
II Generic/ III Generic/ IV Generic/ Generic/
Generic/ 3 4 3 4 3 4 3 3 Generic/ 3 4 3 5
Discipline Discipline Discipline Discipline
Discipline Discipline
Specific Specific Specific Specific
Specific Specific

3.6 Skill 5.6

1.6 Skill 2.6 Skill Enhancemen 4.6 Skill Elective
Enhancem Enhancemen t Course Enhanceme VI 6.6 Extension
2 2 2 2 1 1 2 2 3 4 1 -
ent Course t Course SEC-4, nt Course Generic/ Activity
SEC-1 SEC-2 (Entrepreneu SEC-6 Discipline
rial Skill) Specific

1.7 Skill
2.7 Skill 3.7 Skill 4.7 Skill 6.7
Enhancem
Enhancemen Enhancemen Enhanceme 5.7 Value Professional
ent - 2 2 2 2 2 2 2 2 2 2 2 2
t Course – t Course nt Course Education Competency
(Foundatio
SEC-3 SEC-5 SEC-7 Skill
n Course)
5.8
Summer
3.8 E.V.S. - 1 4.8 E.V.S 2 1 Internship 2
/Industrial
Training
2 3 2 3 2 3 2 3 2 3 2 3
3 0 3 0 2 0 5 0 6 0 1 0

Total – 140 Credits

 Choice Based Credit System (CBCS),
Learning Outcomes Based Curriculum Framework (LOCF)
Guideline Based Credit and Hours Distribution System
for all UG courses including Lab Hours
First Year – Semester-I

Part List of Courses Credit No. of

Hours
Part-1 Language – Tamil 3 6
Part-2 English 3 6
Part-3 Core Courses & Elective Courses [in Total] 13 14
Skill Enhancement Course SEC-1 2 2
Part-4 Foundation Course 2 2
Total 23 30

Semester-II

Part List of Courses Credit No. of

Hours
Part-1 Language – Tamil 3 6
Part-2 English 3 6
Part-3 Core Courses & Elective Courses including laboratory [in Total] 13 14
Part-4 Skill Enhancement Course -SEC-2 2 2
Skill Enhancement Course -SEC-3 (Discipline / Subject Specific) 2 2
Total 23 30

Second Year – Semester-III

Part List of Courses Credit No. of

Hours
Part-1 Language - Tamil 3 6
Part-2 English 3 6
Part-3 Core Courses & Elective Courses including laboratory [in Total] 13 14
Part-4 Skill Enhancement Course -SEC-4 (Entrepreneurial Based) 1 1
Skill Enhancement Course -SEC-5 (Discipline / Subject Specific) 2 2
E.V.S - 1
Total 22 30
 Semester-IV
Part List of Courses Credit No. of
Hours
Part-1 Language - Tamil 3 6
Part-2 English 3 6
Part-3 Core Courses & Elective Courses including laboratory [in Total] 13 13
Part-4 Skill Enhancement Course -SEC-6 (Discipline / Subject Specific) 2 2
Skill Enhancement Course -SEC-7 (Discipline / Subject Specific) 2 2
E.V.S 2 1
Total 25 30

Third Year-Semester-V
Part List of Courses Credit No. of
Hours
Part-3 Core Courses including Project / Elective Based 22 26
Part-4 Value Education 2 2
Internship / Industrial Visit / Field Visit 2 2
Total 26 30

Semester-VI
Part List of Courses Credit No. of
Hours
Part-3 Core Courses including Project / Elective Based & LAB 18 28
Part-4 Extension Activity 1 -
Professional Competency Skill 2 2
Total 21 30

Consolidated Semester wise and Component wise Credit distribution

Parts Sem I Sem II Sem III Sem IV Sem V Sem VI Total Credits
Part I 3 3 3 3 - - 12
Part II 3 3 3 3 - - 12
Part III 13 13 13 13 22 18 92
Part IV 4 4 3 6 4 1 22
Part V - - - - - 2 2
Total 23 23 22 25 26 21 140

*Part I. II, and Part III components will be separately taken into account for CGPA
calculation and classification for the under graduate programme and the other
components. IV, V have to be completed during the duration of the programme as per the
norms, to be eligible for obtaining the UG degree.
 Methods of Evaluation
Continuous Internal Assessment Test
Internal 25 Marks
Assignments
Evaluation
Seminars
Attendance and Class Participation
External End Semester Examination 75 Marks
Evaluation
Total 100 Marks
Methods of Assessment
Recall (K1) Simple definitions, MCQ, Recall steps, Concept definitions

Understand/ MCQ, True/False, Short essays, Concept explanations, Short summary or

Comprehend (K2) overview
Application (K3) Suggest idea/concept with examples, Suggest formulae, Solve problems,
Observe, Explain
Analyze (K4) Problem-solving questions, Finish a procedure in many steps, Differentiate

between various ideas, Map knowledge

Evaluate (K5) Longer essay/ Evaluation essay, Critique or justify with pros and cons

Check knowledge in specific or offbeat situations, Discussion, Debating or

Create (K6)
Presentations

Template for Curriculum Design for UG Programme in B.Sc Information Technology

Credit Distribution for UG Programme in Information Technology
 First Year Semester-I

Hours
Part List of Courses Credit per week
Paper Code
(L/T/P)
Part-I Language – Tamil 3 6
Part-II English 3 6
Part-III 23UITCC01, CC1-Programming in C 4 5
23UITCCP01 CC2-Practical: C Programming lab 3 3
Elective Course -EC1 (Generic / Discipline
6 6
Specific) –Choose from Annexure I
Skill Enhancement Course- SEC1
2 2
Part-IV (Non Major Elective)
Foundation Course FC-
2 2
Fundamentals of Computers
Total 23 30

Hours
Part List of Courses Credit per week
Paper Code
(L/T/P)
Part-I Language – Tamil 3 6
Part-II English 3 6
Part-III 23UITCC02, CC3-Java Programming 4 5
23UITCCP02 CC4-Practical: Java Programming & Data
3 3
Structures lab
Elective Course - EC2 (Generic / Discipline
6 6
Specific) –Choose from Annexure I
Skill Enhancement Course -SEC2 (Non Major
2 2
Elective)
Part-IV
Skill Enhancement Course - SEC3 Choose
2 2
from Annexure II
Total 23 30
 Second Year Semester-III
Hours
Part List of Courses Credit per week
Paper Code
(L/T/P)
Part-I Language – Tamil 3 6
Part-II English 3 6
Part-III 23UITCC03 CC5-Relational Data Base Management 4 5
23UITCCP03 CC6-Practical:RDBMS Lab 3 3
Elective Course- EC3 (Generic / Discipline
6 6
Specific) -Choose from Annexure I
Skill Enhancement Course -SEC4 Choose
1 1
from Annexure II
Part-IV
Skill Enhancement Course -SEC5 Choose
2 2
from Annexure II
Environmental Studies - 1
Total 22 30

Semester-IV
Hours
Part List of Courses Credit per week
Paper Code
(L/T/P)
Part-I Language – Tamil 3 6
Part-II English 3 6
Part-III 23UITCC04 CC7 - .NET Programming 4 4
23UITCCP04 CC8- Practical: .NET Programming Lab 3 3
Elective Course - EC4 (Generic / Discipline
6 6
Specific) Choose from Annexure I
Part-IV Skill Enhancement Course - SEC6 Choose
2 2
from Annexure II
Skill Enhancement Course - SEC7 Choose
2 2
from Annexure II
Environmental Studies 2 1
Total 25 30
 Third Year Semester-V
Hours
Part List of Courses Credit per week
Paper Code
(L/T/P)
23UITCC05 CC9- Python Programming 4 5
Part-III 23UITCCP05 CC10- Practical: Python Programming Lab 4 5
23UITCC06 CC11- Operating Systems 4 5
Elective Course - EC5 ( Discipline Specific)
3 4
Choose from Annexure I
Elective Course – EC6 ( Discipline Specific)
3 4
Choose from Annexure I
23UITCCPR1 CC12-Project with Viva voce 4 5
Part-IV Value Education 2 2
Internship / Industrial Training (Summer
2
vacation at the end of IV semester activity)
Total 26 30

Semester-VI

Hours
Part List of Courses Credit per week
Paper Code
(L/T/P)
Part-III 23UITCC07 CC13-Data Communications and Networking 4 6
23UITCC08 CC14-Data Mining 4 6
23UITCCP06 CC15-Practical: Data Mining Lab 4 6
Elective Course – EC7 ( Discipline Specific) 3 5
Choose from Annexure I
Elective Course – EC8 ( Discipline Specific) 3 5
Choose from Annexure I
Part IV Skill Enhancement Course - SEC8 Choose
2 2
from Annexure II
Part-V Extension Activity 1
Total 21 30

Total Credits: 140

 SUGGESTED CORE COMPONENTS
S.No Paper Code Paper Title
1 23UITCC09 Object Oriented Programming Using C++
2 23UITCCP07 C++ Programming Lab
3 23UITCC10 Data Structures
4 23UITCC11 PHP Scripting
5 23UITCC12 Software Project Management
6 23UITCC13 Software Engineering
7 23UITCCP08 Software Engineering Lab
8 23UITCC14 Software Metrics
9 23UITCC15 Machine Learning
10 23UITCC16 Network Security
11 23UITCC17 Mobile Application Development and more..

Annexure – I

Elective Course (EC1- EC8) (Generic / Discipline Specific)

Generic Specific
S.No Paper Title

1 Mathematics-I

2 Mathematics-II

3 Mathematics Practical

4 Discrete Mathematics-I

5 Discrete Mathematics-II

6 Numerical Methods

7 Optimization Techniques

8 Introduction to Linear Algebra

9 Graph Theory and its Application

10 Numerical Methods-I

11 Numerical Methods-II
 12 Statistical Methods and its Application-I

13 Statistical Methods and its Application-II

14 Statistical Practical

15 Physics-I

16 Physics Practical-I

17 Physics-II

18 Physics Practical-II

19 Digital Logic Fundamentals

20 Nano Technology

21 Accounting
22 Cost and Management Accounting

Discipline Specific

S.No Paper Code Paper Title

1 23UITDE01 Natural Language Processing
2 23UITDE02 Analytics for Service Industry
3 23UITDE03 Cryptography
4 23UITDE04 Big Data Analytics
5 23UITDE05 IOT and its Applications
6 23UITDE06 Human Computer Interaction
7 23UITDE07 Fuzzy Logic
8 23UITDE08 Artificial Intelligence
9 23UITDE09 Robotics and its Applications
10 23UITDE10 Computational Intelligence
11 23UITDE11 Grid Computing
12 23UITDE12 Trends in Computing
13 23UITDE13 Artificial Neural Network
14 23UITDE14 Agile Project Management and more..
[Pl. Note: In Semester-VI - For EC7 and EC8 subjects
Instructional hours may be used as: 5 per cycle]
 Annexure - II

Skill Enhancement Course (SEC1-SEC8)

S.No Paper Code Paper Title

1 23UITSE01 Office Automation
2 23UITSE02 Basics of Internet
3 23UITSE03 Problem Solving Techniques
4 23UITSE04 Multimedia Lab
5 23UITSE05 Fundamentals of Information Technology
6 23UITSE06 Introduction to HTML
7 23UITSE07 Web Designing
8 23UITSE08 Software Testing
9 23UITSE09 Quantitative Aptitude
10 23UITSE10 Multimedia Systems
11 23UITSE11 Advanced Excel

12 23UITSE12 Biometrics

13 23UITSE13 Cyber Forensics

14 23UITSE14 Pattern Recognition

15 23UITSE15 Enterprise Resource Planning
16 23UITSE16 Robotics and Its Applications
17 23UITSE17 Simulation and Modelling
18 23UITSE18 Organization Behaviour and more..

Note: For Semester I & II [if other department select our paper as Non Major Elective
choose from the above Skill Enhancement Course]
 FIRST YEAR – SEMESTER – I
CORE – I: PROGRAMMING IN C
Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
5 0 0 I 4 5 25 75 100
Learning Objectives
LO1 To familiarize the students with the understanding of code organization
LO2 To improve the programming skills
LO3 Learning the basic programming constructs.
Prerequisites:
Unit Contents No. of
Hours
Studying Concepts of Programming Languages- Language
Evaluation Criteria - Language design - Language Categories -
Implementation Methods – Programming Environments - Overview of
I 15
C: History of C- Importance of C- Basic Structure of C Programs-
Executing a C Program- Constants, Variables and Data types -
Operators and Expressions - Managing Input and Output Operations
Decision Making and Branching: Decision Making and Looping -
II 15
Arrays - Character Arrays and Strings
User Defined Functions: Elements of User Defined Functions-
Definition of Functions- Return Values and their Types- Function Call-
III 15
Function Declaration- Categories of Functions- Nesting of Functions-
Recursion
Structures and Unions: Introduction- Defining a Structure- Declaring
Structure Variables Accessing Structure Members- Structure
IV 15
Initialization- Arrays of Structures- Arrays within Structures- Unions-
Size of Structures.
Pointers: Understanding Pointers- Accessing the Address of a
Variable- Declaring Pointer Variables- Initializing of Pointer Variables-
Accessing a Variable through its Pointer- Chain of Pointers- Pointer
V Expressions- Pointer and Scale Factor- Pointer and Arrays- Pointers 15
and Character Strings- Array of Pointers- Pointer as Function
Arguments- Functions Returning Pointers- Pointers to Functions- File
Management in C
TOTAL 75
CO Course Outcomes
CO1 Outline the fundamental concepts of C programming languages, and its features
 CO2 Demonstrate the programming methodology.

CO3 Identify suitable programming constructs for problem solving.

Select the appropriate data representation, control structures, functions and concepts
CO4
based on the problem requirement.
CO5 Evaluate the program performance by fixing the errors.

Textbooks
Robert W. Sebesta, (2012), ―Concepts of Programming Languages‖, Fourth Edition,

Addison Wesley (Unit I : Chapter – 1)
E. Balaguruswamy, (2010), ―Programming in ANSI C‖, Fifth Edition, Tata McGraw

Hill Publications
Reference Books
Ashok Kamthane, (2009), ―Programming with ANSI & Turbo C‖, Pearson
1.
Education
Byron Gottfried, (2010), ―Programming with C‖, Schaums Outline Series, Tata
2.
McGraw Hill Publications
NOTE: Latest Edition of Textbooks May be Used
Web Resources
1. http://www.tutorialspoint.com/cprogramming/

2. http://www.cprogramming.com/

3. http://www.programmingsimplified.com/c-program-examples

4. http://www.programiz.com/c-programming

5. http://www.cs.cf.ac.uk/Dave/C/CE.html

6. http://fresh2refresh.com/c-programming/c-function/

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 3 2 2
CO2 3 3 2 3 2 2
CO3 3 3 3 3 2 2
CO4 3 3 2 3 2 2
CO5 3 3 2 3 2 2
Weightage of
course
contributed to 15 14 11 15 10 10
each PSO
 CORE – II: C Programming Practical
Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
0 0 5 I 4 5 25 75 100
Learning Objectives
LO1 The Course aims to provide exposure to problem-solving through C programming
LO2 It aims to train the student to the basic concepts of the C -Programming language
LO3 Apply different concepts of C language to solve the problem
Prerequisites:
Contents
1. Programs using Input/ Output functions
2. Programs on conditional structures
3. Command Line Arguments
4. Programs using Arrays
5. String Manipulations
6. Programs using Functions
7. Recursive Functions
8. Programs using Pointers
9. Files
10. Programs using Structures & Unions
CO Course Outcomes
CO1 Demonstrate the understanding of syntax and semantics of C programs.

CO2 Identify the problem and solve using C programming techniques.

CO3 Identify suitable programming constructs for problem solving.

CO4 Analyze various concepts of C language to solve the problem in an efficient way.
CO5 Develop a C program for a given problem and test for its correctness.

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 3 2 2
CO2 3 3 2 3 2 2
CO3 3 3 3 3 2 2
CO4 3 3 2 3 2 2
CO5 3 3 2 3 3 2
Weightage of course
contributed toeach PSO
15 14 11 15 11 10
 Foundation Course -I Fundamentals of Computers

Subject Inst. Marks

L T P S Credits
Code Hours CIA External Total
2 0 0 II 2 2 25 75 100
Learning Objectives
LO1 To analyze a problem with appropriate problem solving techniques
To understand the main principles of imperative, functional and logic oriented
LO2
programming languages and
LO3 to increase the ability to learn new programming languages.
Prerequisites: Basic knowledge about programming concepts
Unit Contents No. of
Hours
Introduction: Characteristics of Computers - Evolution of Computers
I Basic Computer Organization: I/O Unit - Storage Unit - Arithmetic 6
Logic Unit - Control Unit - Central Processing Unit
Computer Software: Types of Software - System Architecture
II Computer Languages: Machine Language - Assembly Language - 6
High Level Language - Object Oriented Languages
Problem Solving Concepts: Problem Solving in Everyday life - Types
III of Problems - Problem solving with computers - Difficulties with 6
Problem Solving
Problem Solving concepts for the computer: Constant Variables -
Data Types - Functions -Operators - Expressions and Equations -
IV 6
Organizing the Solution: Analyzing the problem - Algorithm -
Flowchart - Pseudo code
Programming Structure: Structuring a solution - Modules and their
function - Local and Global variables - Parameters - Return values -
V 6
Sequential Logic Structure - Problem solving with Decision - Problem
Solving with Loops
TOTAL 30
CO Course Outcomes
Outline the Computer fundamentals and various problem solving concepts in
CO1
Computers
Describe the basic computer organization, software, computer languages, software
CO2 development life cycle and the need of structured programming in solving a
computer problem
Identify the types of computer languages, software, computer problems and examine
CO3
how to set up expressions and equations to solve the problem.
CO4 Choose most appropriate programming languages, constructs and features to solve the
 problems in diversified domains.
Analyze the design of modules and functions in structuring the solution and various
CO5
Organizing tools in problem solving.
Textbooks
Pradeep K.Sinha and Priti Sinha, (2004) ―Computer Fundamentals‖, Sixth Edition,

BPB Publications. (Unit I : Chapter 1 & 2, Unit II : Chapter 10 & 12)
Maureen Sprankle and Jim Hubbard, (2009) ―Problem Solving and Programming
 Concept, Ninth Edition, Prentice Hall. (Unit III: Chapter 1,2 &3) Unit IV : Chapter 3,
Unit V : Chapter 4,5 ,6,7 & 8)
Reference Books
R.G. Dromey, (2007), ―How to Solve it by Computer‖, Prentice Hall International
1.
Series in Computer Science.
C. S. V. Murthy, (2009), ―Fundamentals of Computers‖, Third Edition, Himalaya
2.
Publishing House.
NOTE: Latest Edition of Textbooks May be Used
Web Resources
1. http://www.tutorialspoint.com/computer_fundamentals/

2. http://www.comptechdoc.org/basic/basictut/

3. http://www.homeandlearn.co.uk/

4. http://www.top-windows-tutorials.com/computer-basics/
https://www.programiz.com/article/flowchart-programming (Algorithm and flow
5.
chart)

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 2 2 3
CO2 3 2 2 2 3 2
CO3 3 3 3 3 2 2
CO4 3 2 2 2 2 3
CO5 3 3 2 2 3 2
Weightage of course
15 12 11 11 12 12
contributed toeach PSO
 FIRST YEAR – SEMESTER – II
CORE – III: JAVA PROGRAMMING
Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
5 0 0 II 4 5 25 75 100
Learning Objectives
LO1 To provide knowledge on fundamentals of object-oriented programming
to have the ability to use the SDK environment to create, debug and run servlet
LO2
programs
Prerequisites: Basic knowledge about programming concepts
Unit Contents No. of
Hours
Fundamentals of Object- Oriented Programming: Introduction –
Object Oriented Paradigm – Concepts of Object – Oriented
Programming – Benefits of OOP – Evolution: Java History- Java
I 15
Features - Differs from C and C++ - Overview of Java Language: Java
Program- Structure – Tokens – Java Statements – Java Virtual Machine
– Command Line Arguments
Constants, Variables and Data Types – Operators and Expressions –
II Decision making and Branching – Looping – Arrays - Strings – 15
Collection Interfaces and classes
Classes objects and methods: Introduction – Defining a class – Method
Declaration – Constructors - Method Overloading – Static Members –
III 15
Nesting of methods – Inheritance – Overriding – Final variables and
methods – Abstract methods and classes
Multiple Inheritance: Defining Interfaces – Extending Interfaces –
Implementing Interfaces – Packages: Creating Packages – Accessing
IV 15
Packages – Using a Package – Managing Errors and Exceptions -
Multithreaded Programming
Layout Managers - JDBC – Java Servlet: - Servlet Environment Role –
V Servlet API – Servlet Life Cycle – Servlet Context – HTTP Support – 15
HTML to Servlet Communication
TOTAL 75
CO Course Outcomes
Outline the basic terminologies of OOP, programming language techniques,
CO1
JDBC and Internet programming concepts
Solve problems using basic constructs, mechanisms, techniquesand technologies of
CO2
Java
Analyse and explain the behavior of simple programs involving different techniques
CO3 such as Inheritance, Packages, Interfaces,Exception Handling and Thread and
technologies such as JDBC and Servlets
 Assess various problem-solving strategies involved in Java todevelop a high-level
CO4
application.
Design GUI based JDBC applications and able to develop Servletsusing suitable
CO5
OOP concepts and techniques
Textbooks
E Balagurusamy(2010), ―Programming with Java‖, Tata McGraw Hill Edition India

Private Ltd, 4th Edition
C Xavier,‖Java Programming – A Practical Approach‖, Tata McGraw Hill Edition

Private Ltd
Reference Books
P.Naughton and H.Schildt (1999), ―Java 2 The Complete Reference‖, TMH, 3rd
3.
Edition
4. Jaison Hunder & William Crawford (2002),‖Java Servlet Programming‖, O'Reilly

5. Jim Keogh (2002), ―J2EE: The Complete Reference‖, Tata McGraw Hill Edition.

NOTE: Latest Edition of Textbooks May be Used

Web Resources
6. http://javabeginnerstutorial.com/core-java/

7. http://www.tutorialspoint.com/java/

8. http://beginnersbook.com/java-tutorial-for-beginners-with-examples/

9. http://www.homeandlearn.co.uk/java/java.html

10. http://www.journaldev.com/1877/servlet-tutorial-java (Unit V : Servlet API)

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 2 2 2
CO2 2 3 2 2 2 2
CO3 2 3 3 3 2 2
CO4 2 3 2 2 2 2
CO5 3 3 2 2 2 2
Weightage of course
contributed toeach PSO 12 14 11 11 10 10

CORE – IV: Java Programming & Data Structures lab

Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
0 0 5 II 4 5 25 75 100
 Learning Objectives
To design and develop applications using different Java programming language
LO1
techniques, JDBC & Servlets
LO2 To organize and manipulate the data with the help of fundamental data structures
Prerequisites:
Contents
1. Basic Programs
2. Arrays
3. Strings
4. ArrayList, HashSet and Vector collection classes
5. Classes and Objects
6. Interfaces
7. Inheritance
8. Packages
9. Exception Handling
10. Threads
11. Linked List
12. Stacks
13. Queue
14. Sorting
15. Binary Tree Representation
16. Working with Database using JDBC
17. Web application using Servlet
CO Course Outcomes
CO1 Identify and explain the way of solving the simple problems

Use appropriate software development environment to write, compile and execute

CO2
object-oriented Java programs
Analyze and identify necessary mechanisms of Java needed to solve real-world
CO3
problem
CO4 Test for defects and validate a Java program with different inputs
Design, develop and compile Core Java , GUI , JDBC and servlet applications that
CO5
utilize OOP and data structure concepts

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 3 3 2 2
CO2 3 3 3 3 2 2
CO3 3 3 3 2 2 3
CO4 3 3 3 3 3 2
CO5 3 3 2 3 2 2
Weightage of course
contributed toeach PSO 15 14 14 14 11 11
 SECOND YEAR – SEMESTER – III
CORE – V: Relational Database Management System

Marks
Subject Inst.
L T P S Credits
Code Hours
CIA External Total

5 0 0 III 4 5 25 75 100

Learning Objectives

LO1 To understand the basic DBMS models and architecture

LO2 To learn how to query and normalize the database.

To study the data base design, transaction Processing and Management and Security
LO3
Issues.

Prerequisites: base knowledge about data and information

Unit Contents No. of

Hours

Introduction to Databases: Introduction – Characteristics of the Database

Approach – Actors on the Scene – Workers behind the scene –
Advantages of using DBMS Approach. Overview of database and
I Architectures: Data Models, Schemas, and Instances – Three-schema 15
Architecture and Data Independence – Database languages & Interfaces –
Database System Environment– Centralized & Client Server Architecture
for DBMS - Classification of DBMS.

Basic Relational Model: Relational Model Concepts – Relational Model

Constraints and Relational Database Schemas – Update Operations,
Tractions, Dealing with Constraint Violations – Formal Relational
Languages: Unary Relational Operations: SELECT and PROJECT –
II Relational Algebra Operations from Set Theory – Binary Relational 15
Operations: JOIN and DIVISION – Examples of Queries in Relational
Algebra.

Conceptual Data Modeling using the ER Model: Using High-Level

Conceptual Data Models for Database Design – An example DB
application – Entity Types, Entity Sets, Attributes, and Keys –
III 15
Relationship Types, Relationship sets, Roles, and Structural Constraints –
Weak entity types – Example- Mapping a Conceptual Design into Logical
Design: Relational Database Design using ER- Relational Mapping –
 Mapping EER Model Constructs to Relations

Functional Dependencies and Normalization for Relational Database:

Functional Dependencies – Definition of Functional Dependency –
IV Normal Forms based on Primary Keys – Normalization of Relations – 15
First Normal Form – Second Normal Form – Third Normal Form –
BCNF- Fourth Normal Form- Fifth Normal Form.

SQL: The Relational Database Standard: Data definition, Constraints, and

schema changes in SQL – Basic Queries in SQL – More complex SQL
Queries – Insert, delete and update statements in SQL – Views in SQL.

PL/SQL: Introduction to PL/SQL – More on PL/SQL – Error Handling in

V PL/SQL – Oracle‗s Named Exception Handlers – Stored Procedures and 15
Functions – Execution of Procedures and Functions – Advantages –
Procedures Vs. Functions – Syntax for Creating Procedures and Functions
– Deleting a Stored Procedure or Function – Oracle Packages – Database
Triggers – Types Of Triggers – Deleting a Trigger – Raise-Application
Error Procedure

TOTAL 75

THEORY 100%

CO Course Outcomes

CO1 Outline the fundamental RDBMS concepts and PL/SQL

CO2 Apply database operations, mapping, normalization, SQL and PL/SQL

CO3 Analyze the requirements to implement relational database concepts

CO4 Evaluate the database based on various models and normalization.

Design and construct normalized tables and manipulate it effectively using SQL and
CO5
PL/SQL database objects

Textbooks

 Ramez Elmasri, Shamkant B. Navathe (2014), ―Database Systems‖, Sixth edition,

Pearson Education, New Delhi.

 Ivan Bayross (2003 Reprint), SQL, PL/SQL-The Programming Language of Oracle,

Second Revised Edition, BPB Publications, New Delhi.

Reference Books

1. Abraham Silberschatz, Henry F.Korth, S.Sudarshan, Database System Concepts, Tata

McGraw Hill Publication, 4th Edition.
NOTE: Latest Edition of Textbooks May be Used

Web Resources

1. http://srikanthtechnologies.com/books/orabook/ch1.pdf

2. Http://www.tmv.edu.in/pdf/Distance_education/BCA%20Books/BCA%20IV%20SEM/B
C A-428%20Oracle.pdf

3. http://www.tutorialspoint.com/sql/sql-rdbms-concepts.htm

4. http://ecomputernotes.com/database-system/rdbms

5. http://www.mithunashok.com/2011/04/basics-of-rdbms.html

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 3 3 3
CO2 3 3 2 3 3 3
CO3 3 3 3 3 3 2
CO4 3 3 2 3 3 3
CO5 3 3 2 3 3 2
Weightage of course
contributed toeach PSO 15 14 11 15 15 13

CORE – VI: RDBMS- PRACTICAL

Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
0 0 4 III 4 4 25 75 100
Learning Objectives
LO1 The primary Objective of this paper is to learn and implement SQL & PL/SQL.
Prerequisites:
Contents
SQL:
1. DDL Commands
2. DML Commands
3. DCL Commands
4. SQL Built-in functions
5. Using Sub Queries
PL/SQL:
6. Simple programs using PL/SQL
7. Procedures
8. User-defined functions
9. Exception Handling
10. Triggers

CO Course Outcomes
CO1 Choose appropriate SQL queries and PL/SQL blocks for the database.

CO2 Implement SQL and PL/SQL blocks for the given problem effectively.

CO3 Analyse the problem and Exceptions using queries and PL/SQL blocks.
CO4 Validate the database for normalization using SQL and PL/SQL blocks.
CO5 Design Database tables, create Procedures, user-defined functions and Triggers.

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 2 2 2 3 3 2
CO2 3 3 2 3 2 3
CO3 2 3 3 3 2 3
CO4 2 3 2 3 3 3
CO5 2 2 2 3 3 2
Weightage of course
contributed toeach PSO 11 13 11 15 13 13
SECOND YEAR –SEMESTER- IV

CORE – VIII: .NET PROGRAMMING

Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
5 0 0 IV 4 5 25 75 100
Learning Objectives
To provide sufficient knowledge in developing web applications using C# and
LO1
ASP.NET
LO2 To manipulate data from SQL Server using Microsoft ADO.NET.
Prerequisites:
Unit Contents No. of
Hours
The Creation of C#: C# Relates to the .Net Framework - Common
Language Runtime - Managed vs unmanaged code - An Overview of
C#: Object-Oriented Programming - First Simple Program-Handling
I 15
Syntax errors - Using code blocks-semicolon, positioning and
Indentation-The C# Keywords-Identifiers-The .Net Framework Class
Library-Data Types, Literals and Variables- Operators.
Program Control Statements: If Statement- switch Statement-For
Loop- While loop do-while loop- foreach loop-using break to exit a loop-
II using continue- goto- Introducing Classes and objects: Class 15
Fundamentals- objects creation-Methods-constructors-Garbage
Collection and Destructors-Exception Handling.
Arrays and Strings: Arrays-Multidimensional Arrays-Jagged Arrays-
for each loop Strings- Methods and classes: Method overloading- Main
III 15
Method-Recursion-static Classes Delegates,Events and Lambda
Expressions: Delegates -Lambda Expressions-LINQ
Developing ASP.NET Applications: Visual Studio: Creating Websites-
The Anatomy of a Web Form – Web Form Fundamentals: Converting
IV HTML Page to an ASP.Net Page – Page Class – Web Controls. State 15
Management: View State - Transferring Information between Pages –
Cookies – Session State – Application State.
Validation Controls – AdRotator Control. Working with Data:
ADO.NET Fundamentals:– Direct Data Access – Disconnected Data
Access - Data Binding: Data Binding with ADO.NET –Data Source
V 15
Controls - The Data Controls: The GridView – Formatting the GridView
– Selecting GridView Row – Editing, Sorting and Paging the GridView-
Generating Crystal Reports.
TOTAL 75
THEORY 80% & PROGRAM 20%
CO Course Outcomes
CO1 Outline the features of C# programming language and ASP.NET applications

CO2 Demonstrate the salient properties of C# and ASP.NET applications

CO3 Identify the various stages in developing a web forms

CO4 Select the appropriate controls to create a web form.
CO5 Recommend a data driven web application by connecting to the data sources

Textbooks
 Herbert Schildt (2010), C# 4.0 The Complete Reference, Tata McGraw-Hill Pvt Ltd

 Mathew MacDonald, (2010), Beginning ASP.NET 4 in C# 2010, Second Edition,

 Apress.

Reference Books
1. Greg Buczek (2002), ―ASP.NET – Developer‗s guide‖, Tata MaGraw Hill Publication

2. Jesse Liberty, (2002), ―Programming C#, 3.0‖, O‗Reilly Press

3. J.Sharp (2009), ―Microsoft Visual C# 2008 Step by Step‖, PHI Learning Private Ltd.

4. Christian Nagel et al. , ―Professional C# 2005 with .NET 3.0‖, Wiley India, 2007

NOTE: Latest Edition of Textbooks May be Used

Web Resources
1. http://ssw.jku.at/Teaching/Lectures/CSharp/Tutorial/

2. http://www.csharpkey.com/csharp/

3. http://www.w3schools.com/aspnet/default.asp

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 3 3 3
CO2 3 3 2 3 3 3
CO3 3 3 3 3 3 3
CO4 3 3 2 3 3 3
CO5 3 3 2 3 3 3
Weightage of course
contributed toeach PSO 15 14 11 15 15 15
CORE –VII: .NET PROGRAMMING LAB
Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
0 0 4 IV 4 4 25 75 100
Learning Objectives
To provide sufficient knowledge in developing web applications and to
LO1
manipulate data from SQL Server using Microsoft ADO.NET.
Prerequisites:
Contents
Exercises
1. C# Basics
2. Looping Constructs
3. Arrays & Jagged Array
4. Strings
5. Classes and Objects
6. Method overloading
7. Delegates
 8. LINQ
9. Lambda Expressions

CO Course Outcomes
CO1 Demonstrate MS Visual Studio.NET IDE to Create applications.

CO2 Apply C# and ASP.NET concepts to design applications.

Simplify the functionality of the web application in accordance to the user
CO3
Requirement.
CO4 Evaluate the web application to fix the errors.
CO5 Build a web application using C# and ASP.NET concepts to solve the problem

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 3 3 3
CO2 3 3 2 3 3 3
CO3 3 3 3 3 3 3
CO4 3 3 2 3 3 3
CO5 3 3 2 3 3 3
Weightage of course
contributed toeach PSO 15 14 11 15 15 15
THIRD YEAR –SEMESTER- V

CORE – IX: CORE 9: PYTHON PROGRAMMING

Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
CC9 5 0 0 V 4 5 25 75 100
Learning Objectives
LO1 Understand the concepts of Python programming.
LO2 To apply the OOPs concept in PYTHON programming.
LO3 To impart knowledge on demand and supply concepts
LO4 Learn to solve basic programming problems.
Unit Contents No. of
Hours
Basics of Python Programming: History of Python-Features
of Python-Literal-Constants-Variables - Identifiers–Keywords-
Built-in Data Types-Output Statements – Input Statements-
I 15
Comments – Indentation- Operators-Expressions-Type
conversions. Python Arrays: Defining and Processing Arrays
– Array methods.
Control Statements: Selection/Conditional Branching 15
statements: if, if-else, nested if and if-elif-else statements.
II Iterative Statements: while loop, for loop, else suite in loop and
nested loops. Jump Statements: break, continue and pass
statements.
 Functions: Function Definition – Function Call – Variable Scope 15
and its Lifetime-Return Statement. Function Arguments:
Required Arguments, Keyword Arguments, Default Arguments
and Variable Length Arguments- Recursion. Python Strings:
III
String operations- Immutable Strings - Built-in String Methods
and Functions - String Comparison. Modules: import statement-
The Python module – dir() function – Modules and Namespace –
Defining our own modules.
Lists: Creating a list -Access values in List-Updating values in 15
Lists-Nested lists -Basic list operations-List Methods. Tuples:
Creating, Accessing, Updating and Deleting Elements in a tuple –
IV Nested tuples– Difference between lists and tuples. Dictionaries:
Creating, Accessing, Updating and Deleting Elements in a
Dictionary – Dictionary Functions and Methods - Difference
between Lists and Dictionaries.
Python File Handling: Types of files in Python - Opening and 15
Closing files-Reading and Writing files: write() and writelines()
methods- append() method – read() and readlines() methods –
V with keyword – Splitting words – File methods - File Positions-
Renaming and deleting files.

TOTAL 75
CO Course Outcomes
CO1 Outline the basic concepts in python language.

CO2 Interpret different looping and conditional statements in python language

Apply the various data types and identify the usage of control statements, loops, functions
CO3
and Modules in python for processing the data
CO4 Analyze and solve problems using basic constructs and techniques of python.
CO5 Assess the approaches used in the development of interactive application.
Textbooks
Reema Thareja, ―Python Programming using problem solving approach‖, First Edition,

2017, Oxford University Press.
Dr. R. Nageswara Rao, ―Core Python Programming‖, First Edition, 2017, Dream tech

Publishers
Reference Books
1. VamsiKurama, ―Python Programming: A Modern Approach‖, Pearson Education.
2. Mark Lutz, ‖Learning Python‖, Orielly.
NOTE: Latest Edition of Textbooks May be Used
Web Resources
1. https://www.programiz.com/python-programming
2. https://www.guru99.com/python-tutorials.html
 MAPPING TABLE

CO/ PSO PSO1 PSO2 PSO3 PSO4 PSO5 PSO6

CO1 3 2 2 3 2 2
CO2 2
2 3 3 2 2
CO3 2 3 2 2 3 1
CO4 1 2 2 1 3 2
CO5 2 2 2 1 3 3
Weightage of
course contributed
to each
PSO 10 12 10 10 13 10

CORE 10: PYTHON PROGRAMMING-LAB

Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
CC10 0 0 5 V 4 5 25 75 100
Learning Objectives
Understand the fundamentals of programming using Python, such as variables, data
LO1
types, control structures, and functions.
LO2 Learn how to use Python libraries and modules to solve problems.
Practice writing Python code to solve real-world problems and build basic
LO3
applications.
Gain experience with common programming paradigms, such as object-oriented
LO4
programming and functional programming.
LO5 Understand best practices for debugging and testing code.
List of Exercises
1. Program using variables, constants, I/O statements in Python.
2. Program using Operators in Python.
3. Program using Conditional Statements.
4. Program using Loops.
5. Program using Jump Statements.
6. Program using Functions.
7. Program using Recursion.
8. Program using Arrays.
9. Program using Strings.
10. Program using Modules.
11. Program using Lists.
12. Program using Tuples.
13. Program using Dictionaries.
14. Program for File Handling.
 TOTAL 75
CO Course Outcomes
Understand the significance of control statements, loops and functions in creating
CO1
Simple programs.

CO2 Interpret the core data structures available in python to store, process and sort the data.

CO3 Develop the real time applications using python programming language.

CO4 Analyze the real time problem using suitable python concepts.

CO5 Assess the complex problems using appropriate concepts in python.

MAPPING TABLE

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 3 2 3 3
CO2 3 3 2 2 3 3
CO3 3 2 2 3 3 2
CO4 3 2 3 3 2 2
CO5 3 3 3 3 3 2
Weightage of
course
contributedto
each 15 12 13 13 14 12
PSO

CORE – XI: OPERATING SYSTEMS

Subject Inst. Marks

L T P S Credits
Code Hours CIA External Total
5 0 0 V 4 5 25 75 100
Learning Objectives
The objective of this course is to provide an introduction to the internal
LO1 operation of modern operating systems

To focus on the core concepts such as processes and threads, mutual exclusion,
LO2 CPU scheduling, deadlock, memory management, and file systems.
 Prerequisites:
Unit Contents No. of
Hours
Introduction: Definition of Operating System - OS Structures: OS
Services - System Calls - Virtual Machines - Process
I Management: Process Concept - Process Scheduling - Operation 15
on Processes - Co-operating Processes - Inter-process
Communication
CPU Scheduling: Basic Concepts - Scheduling Criteria -
Scheduling Algorithms - Process Synchronization: The Critical
II 15
Section Problem - Semaphores - Classical Problems of
Synchronization - Critical Regions
Deadlocks: System Model - Deadlock characterization – Methods
III for Handling Deadlocks Deadlock Prevention - Deadlock 15
avoidance- Deadlock Detection - Recovery from Deadlock.
Storage management: Memory management - Swapping –
Contiguous Memory allocation. Paging – Segmentation –
IV Segmentation with Paging –Virtual memory: Demand paging - 15
Page replacement – Thrashing. Mass-Storage Structure: Disk
Structure- Disk scheduling.
File-System Interface: File Concept-File Attributes-File
Operations – Access Methods: Sequential Access – Direct Access
–Directory Structure: Single-Level Directory- Two –Level
V 15
Directory-Tree-Structured Directories- Introducing Shell
Programming – Linux General Purpose Commands-Process
Oriented Commands – Communication Oriented Commands

TOTAL 75
CO Course Outcomes
CO1 Outline the fundamental concepts of an OS and their respective functionality

CO2 Illustrate the importance of open source operating system commands

CO3 Identify and stimulate management activities of operating system

CO4 Analyze the various services provided by the operating system.
Interpret different problems related to Process, Scheduling, Deadlock, memory
CO5
and Files
Textbooks
Abraham Silberschatz, Peter Baer Galvin, Greg Gagne (2012), ―Operating

System Concepts‖, 9th edition, Wiley Student Edition.
 B.Mohamed Ibrahim, (2005), ―Linux Practical Approach‖,Firewall Media

Reference Books
 Milan Milenkovic (2003), ―Operating System Concepts and Design‖, McGraw
1.
Hill.
Andrew S. Tanenbaum, (2001), ―Modern Operating Systems‖, 2nd Edition,
2.
Prentice Hall of India.
Deital and Deital (1990), ―Introduction to Operating System‖, Pearson
3.
Education.
4. William Stallings (1997), ―Operating Systems‖, Prentice Hall of India.

NOTE: Latest Edition of Textbooks May be Used

Web Resources
1. http://www.tutorialspoint.com/operating_system/

2. http://www.reallylinux.com/docs/files.shtml

3. http://www.tutorialspoint.com/operating_system/os_linux.htm

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 3 3 3
CO2 3 3 2 3 3 3
CO3 3 3 3 3 3 3
CO4 3 3 2 3 3 3
CO5 3 3 2 3 3 3
Weightage of course
contributed toeach PSO 15 14 11 15 15 15

THIRD YEAR – SEMESTER – VI

CORE – XIII: DATA MINING
Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
5 0 0 VI 4 5 25 75 100
Learning Objectives
To identify the underlying concepts and the fundamental data mining methodologies
LO1
with the ability to formulate and solve problems
Prerequisites:
Unit Contents No. of
Hours
Introduction: Data Mining – Kinds of Data and Patterns to be Mined –
Technologies used –Kinds of Applications are Targeted - Major Issues –
I Data objects and Attribute types – Basic statistical Descriptions of Data- 15
Data Preprocessing : Data Cleaning – Data Integration - Data Reduction
- Data Transformation.
 Association Rules Mining: Introduction – Frequent Itemset Mining
Methods: Apriori Algorithm-Generating Association Rules from Frequent
II 15
Itemsets-Improving the efficiency of Apriori-A Pattern –Growth
Approach for mining Frequent Itemsets-Pattern Evaluation Methods.
Classification: Introduction –Basic concepts – Logistic regression -
III Decision tree induction–Bayesian classification, Rule–based 15
classification-Model Evaluation and selection.
Cluster Analysis: Introduction-Requirements for Cluster Analysis -
Partitioning Methods: The K-Means method - Hierarchical Method:
IV Agglomerative method - Density based methods: DBSCAN-Evaluation 15
of Clustering: Determining the Number of Clusters – Measuring
Clustering Quality.
Outlier Detection: Outliers and Outlier Analysis – Outlier Detection
Methods - Data Visualization: Pixel-oriented visualization – Geometric
Projection visualization technique-
V 15
Icon-based-Hierarchical visualization-Visualizing complex data and
relations.

TOTAL 75
CO Course Outcomes
CO1 Outline the fundamentals and the principles of Data Mining

CO2 Apply suitable different preprocessing for data mining

CO3 Classify data-mining techniques based on the different applications

CO4 Analyze the various data mining algorithms with respect to functionality
Recommend appropriate data models for data mining techniques to solve real world
CO5 problems

Textbooks
Jiawei Han, Micheline Kamber, Jian Pei, ―Data Mining concepts and techniques‖, 3rd
 Edition, Elsevier publication, 2012.

Reference Books
Ian H. Witten and Eibe Frank, (2005), ―Data Mining: Practical Machine Learning Tools
1.
and Techniques (Second Edition)‖, Morgan Kaufmann.
2. Arun K Pujari, ―Data Mining Techniques‖, 10 impression, University Press, 2008.
Daniel T. Larose , Chantal D. Larose, "Data mining and Predictive analytics," Second
3.
Ed., Wiley Publication, 2015.
G.K. Gupta, ―Introduction to Data mining with case studies‖, 2nd Edition, PHI Private
4.
limited, New Delhi, 2011.
NOTE: Latest Edition of Textbooks May be Used
Web Resources
1. http://csed.sggs.ac.in/csed/sites/default/files/WEKA%20Explorer%20Tutorial.pdf
2. https://www.cs.auckland.ac.nz/courses/compsci367s1c/tutorials/IntroductionToWeka.pdf

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 2 2 2 2 3 3
CO2 3 3 2 3 3 2
CO3 2 3 3 2 3 3
CO4 3 3 2 2 3 3
CO5 3 3 2 2 3 3
Weightage of course
contributed toeach PSO 13 14 11 11 15 14

CORE – XIV: DATA MINING LAB

Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
0 0 6 VI 4 6 25 75 100
Learning Objectives
Understand the data sets, data preprocessing and demonstrate the working of algorithms
LO1 for data mining tasks such as association rule mining, classification, clustering and
regression.
Prerequisites:
Contents
1. Understanding the data
2. Visualization Techniques
3. Data Preprocessing
4. Handling Missing Values
5. Data Reduction-Principal Component Analysis
6. Data Normalization-Min-Max, Z-score, Decimal Scaling
7. Association Rule Mining-Apriori Algorithm
8. Classification
9. Logistic Regression
10. Decision Tree
11. Naive Bayesian
12. Clustering
13. K-Means Clustering
14. DBSCAN
15. Agglomerative
16. Case Study

CO Course Outcomes
CO1 Understand the real time datasets for analysis
CO2 Apply suitable preprocessing for data mining task
CO3 Demonstrate data-mining techniques based on the different applications
CO4 Analyze the performance evaluation of various data mining algorithms
Prescribe appropriate data models for data mining techniques to solve real world
CO5 problems

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 2 2 2 2 3 3
CO2 3 3 2 3 3 2
CO3 2 3 3 2 3 3
CO4 3 3 2 2 3 3
CO5 3 3 2 2 3 3
Weightage of course
contributed toeach PSO 13 14 11 11 15 14
CORE – XV: DATA COMMUNICATION AND NETWORKING
Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
5 0 0 VI 4 5 25 75 100
Learning Objectives
This course is to provide students with an overview of the concepts and fundamentals
LO1
of data communication and computer networks
LO2 To familiarize the student with the basic taxonomy and terminology of the computer.
Prerequisites:
Unit Contents No. of
Hours
Introduction: Data Communication-Networks: Distributed Processing-
Network Criteria Physical Structures –Network Models-Categories of
I Network-Internetwork - The Internet 15
Protocols and Standards – Network Models: Layers in the OSI Model -
TCP/IP Protocol Suite.
Data and Signals: Analog and Digital Data - Analog and Digital Signals
– Performance - Digital Transmission: Transmission Modes –
II 15
Multiplexing: FDM – WDM - Synchronous TDM -Statistical TDM -
Transmission Media: Guided media - Unguided Media.
 Switching: Circuit Switched Networks - Datagram Networks-Virtual
Circuit Network - Error Detection and Correction: Introduction - Block
III Coding - Linear Block Codes - Cyclic Codes: Cyclic Redundancy 15
Check - Checksum. Data Link Control: Framing - Flow Control and
Error Control - Noiseless Channel: Stop-and-wait Protocol.
Wired LANs: Standard Ethernet-GIGABIT Ethernet-Wireless LAN:
Bluetooth Connecting LANs: Connecting Devices: Passive Hubs-
IV Repeaters-Active Hubs-Bridges-Two Layer Switches-Routers-Three 15
layer Switches-Gateway-Network Layer: Internet Protocol: IPv4 –
Ipv6-Transition from IPv4 to IPv6.
Network Layer: Delivery, Forwarding and Routing- Unicast Routing
Protocols: Distance Vector Routing-Link state routing- Future &
Current Trends in Computer Networks: 5G Network: Salient Features-
V Technology-Applications-Advanced Features-Advantages & 15
Disadvantages-Internet of Things: key Features -Advantages &
Disadvantages-IOT Hardware- IOT Technology and Protocols-IOT
Common Uses-Applications-WiFi-WiMax Lifi- Lifi vs Wifi.
TOTAL 75
THEORY 20% & PROBLEM 80%
CO Course Outcomes
CO1 Understand the fundamental concepts of computer networks and its application areas

Identify and use various networking techniques and components to establish

CO2
networking connection and transmission
Analyze the services performed by different network layers and recent advancements
CO3
in networking
CO4 Compare various networking models, layers, protocols and technologies.
CO5 Select the appropriate networking mechanisms to build a reliable network

Textbooks
Behrouz and Forouzan,(2006), Data Communication and Networking‖, 4th Edition,

TMH.
 Ajit Pal,(2014), Data Communication and Computer Networks, PHI.

Reference Books
Jean Walrand (1998), ―Communication Networks,Second Edition‖, TataMcGraw
1.
Hill.
NOTE: Latest Edition of Textbooks May be Used
Web Resources
1. http://www.tutorialspoint.com/data_communication_computer_network/

2. http://www.slideshare.net/zafar_ayub/data-communication-and-network-11903853
3. http://www.freetechbooks.com/data-communication-and-networks-f31.html

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 3 3 2
CO2 3 3 2 3 3 2
CO3 3 3 3 3 3 2
CO4 3 3 2 3 3 2
CO5 3 3 2 3 3 2
Weightage of course
contributed toeach PSO 15 14 11 15 15 10
 SUGGESTED TOPICS IN CORE COMPONENT
S.NO PAPER CODE PAPER TITLE
1 23UITCC09- OBJECT ORIENTED PROGRAMMING USING C++
2 23UITCCP07- C++ PROGRAMMING LAB
3 23UITCC10- DATA STRUCTURES
4 23UITCC11- PHP SCRIPTING
5 23UITCC12- SOFTWARE PROJECT MANAGEMENT
6 23UITCC13- SOFTWARE ENGINEERING
7 23UITCCP08- SOFTWARE ENGINEERING LAB
8 23UITCC14- SOFTWARE METRICS
9 23UITCC15- MACHINE LEARNING
10 23UITCC16- NETWORK SECURITY
11 23UITCC17- MOBILE APPLICATION DEVELOPMENT AND MORE..

OBJECT ORIENTED PROGRAMMING USING C++

Subject Inst. Marks

L T P S Credits
Code Hours CIA External Total
5 0 0 - 4 5 25 75 100
Learning Objectives
LO1 To inculcate knowledge on Object-oriented concepts and programming using C++.
LO2 Demonstrate the use of various OOPs concepts with the help of programs
Unit Contents No. of
Hours
OOP Paradigm – Concepts of OOP – Benefits of OOP - Object 15
Oriented Languages – Applications of OOP – OOP Design: Using
I
UML as a Design Tool Beginning with C++

Tokens, Expressions and Control Structures - Functions in C++ : 15

Function Prototyping – Call by Reference - Return by Reference –
II
Inline Function – Default Arguments – Const Arguments – Recursion
– Function Overloading – Classes and Objects
Constructors and Destructors: Constructors – Parameterized 15
III Constructors – Multiple Constructors – Constructor with default
Arguments – Copy Constructors – Dynamic Constructor – Destructors
 – Operator Overloading and Type Conversions: Operator Overloading
– Overloading Unary Operators – Overloading Binary operators –
Rules for Operator Overloading – Type Conversions

Inheritance: Introduction – Types of Inheritance – Virtual Base Classes 15

IV – Abstract Classes – Pointers - Virtual Function - Polymorphism

Templates: Class Templates – Function Templates – Overloading of

V template Function – Exception Handling 15

TOTAL 75
CO Course Outcomes
Outline the C++ programming fundamentals and the concepts of object-oriented
CO1
programming like object and class, Encapsulation, inheritance and polymorphism.
Classify the control structures, types of constructors, inheritance and different type
CO2
conversion mechanisms.
Analyze the importance of object oriented programming features like polymorphism,
CO3 reusability, generic programming, data abstraction and the usage of exception
handling.
Determine the use of object oriented features such as classes, inheritance and
CO4
templates to develop C++ programs for complex problems.
Create a program in C++ by implementing the concepts of object-oriented
CO5
programming.
Textbooks
E. Balaguruswamy, (2013), ―Object Oriented Programming using C++‖, 6th Edition,

Tata McGraw Hill.
Reference Books
Bjarne Stroustrup, ―The C++ Programming Language‖, Fourth Edition, Pearson
1
Education.
Hilbert Schildt, (2009), ―C++ - The Complete Reference‖, 4th Edition, Tata
2
McGrawHill
NOTE: Latest Edition of Textbooks May be Used
Web Resources
1. http:/fahad.cprogramming.blogspot.com/p/c-simple-examples.html
2. http://www.sitesbay.com/cpp/cpp-polymorphism

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 3 3 2
CO2 3 3 2 3 3 2
CO3 3 3 3 3 3 2
CO4 3 3 2 3 3 2
CO5 3 3 2 3 3 2
 Weightage of course
contributed toeach PSO 15 14 11 15 15 10

C++ Programming Lab

Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
0 0 5 - 4 5 25 75 100
Learning Objectives
LO1 To inculcate knowledge on Object-oriented concepts and programming using C++.
LO2 Demonstrate the use of various OOPs concepts with the help of programs
List of Excercises
Exercises:
1. Working with Classes and Objects
2. Using Constructors and Destructors
3. Using Function Overloading
4. Using Operator Overloading
5. Using Type Conversions
6. Using Inheritance
7. Using Polymorphism
8. Using Console I/O
9. Using Templates
10. Using Exceptions
TOTAL 75
CO Course Outcomes
CO1 Understand the fundamentals of C++ programming structure

Identify the basic features of OOPS such as classes, objects, polymorphism,

CO2
inheritance
Analyze the concept of inheritance with the understanding of early and late binding,
CO3 usage of exception handling, constructors, destructors, generic programming and type
conversions
Determine the use of various data structures such as stacks, queues and lists to solve various
CO4
computing problems in C++ by incorporating OOPS concepts.
Develop a program in C++ with the concepts of object oriented programming to solve real-world
CO5
problems.

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 3 3 2
CO2 3 3 2 3 3 2
CO3 3 3 3 3 3 2
CO4 3 3 2 3 3 2
CO5 3 3 2 3 3 2
 Weightage of course
contributed toeach PSO 15 14 11 15 15 10

DATA STRUCTURES
Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
4 0 0 II 4 4 25 75 100
Learning Objectives
LO1 To become familiar with the various data structures and their applications
LO2 to increase the understanding of basic concepts of the design and use of algorithms
Prerequisites:
Unit Contents No. of
Hours
Introduction and overview: Basic Terminology – Data Structures –
Operations - Algorithms: Complexity – Time Space – Algorithmic
I 12
Notation – Control Structures – Complexity of Algorithms – Notations
Arrays: Representation – Operations - Linear Search – Binary Search
Stack: Representation – Arithmetic expressions: Polish Notation –
Recursion: Towers of Hanoi - Queue –Priority Queue - Linked Lists:
II 12
Introduction – Representation of Linked Lists – Traversing a Linked
Lists – Searching a Linked List
Insertion into a Linked List – Deletion into Linked List – Header Linked
III Lists – Two-way Lists –Doubly Linked List - Trees : Binary Trees – 12
Representation – Traversal using Recursion – Binary Search Trees
Sorting : Bubble Sort Insertion Sort, Selection Sort, Merge Sort, Quick
IV 12
Sort, Heap Sort
Graph – Graph Theory Terminology –Sequential Representation –
Warshalls Algorithm – Shortest Path – Linked Representation -
V 12
Traversals – Dynamic Programming – All Pairs Shortest Path - Greedy
– Knapsack – Back Tracking – 8 Queens
TOTAL 60
THEORY 100%
CO Course Outcomes
CO1 Outline the different fundamental concepts of data structures

Make use of different memory representation for data storage and apply various
CO2
operations
CO3 Construct an algorithm for different data structure operations.
CO4 Analyse the data structures applications.
CO5 Discover suitable techniques to provide solution for solving the problems.
 Textbooks
Seymour Lipschutz (1986), ―Theory and Problems of Data Structures‖, Tata McGraw-

Hill Edition
Reference Books
E.Horowitz, S.Sahni, S.Rajasekaran (1998), ―Computer Algorithms‖, Galgotia
1.
Publications.
Robert Kruse, C.L.Tondo, Bruce Leung, ―Data Structures and Program Design in C‖,
2.
Second Edition, Prientice Hall Publications
NOTE: Latest Edition of Textbooks May be Used
Web Resources
1. http://www.cs.sunysb.edu/~skiena/214/lectures/

2. http://datastructures.itgo.com/graphs/dfsbfs.htm

3. http://oopweb.com/Algorithms/Documents/PLDS210/VolumeFrames.html

4. http://discuss.codechef.com/questions/48877/data-structures-and-algorithms

5. http://code.tutsplus.com/tutorials/algorithms-and-data-structures--cms-20437
ttps://www.tutorialspoint.com/data_structures_algorithms/insertion_sort_algorithm.htm
6.
(Unit IV : Insertion Sorting)

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 3 3 3
CO2 3 3 2 3 3 3
CO3 3 3 3 3 3 2
CO4 3 3 2 3 3 3
CO5 3 3 2 3 3 2
Weightage of course
contributed toeach PSO 15 14 11 15 15 13

PHP SCRIPTING – PRACTICAL

Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total
0 0 5 V 4 5 25 75 100
Learning Objectives
To enable the students to understand, analyze and build dynamic webpages using
LO1
PHP and jQuery with MySql database
Prerequisites:
Unit Contents No. of
 Hours
Introduction to PHP : Language Basics : Lexical Structure – Data
Types – Variables - Expressions and Operators – Flow – Control
statements – Embedding PHP in Web Pages
I 15
Exercises:
1. Control Structures
2. Working with Forms.
Functions : Defining a function – Variable Scope - Function Parameters
– Strings : Encoding and Escaping – Comparing Strings – Manipulating
and Searching Strings – Arrays: Single and Multidimensional Arrays –
Traversing Arrays – Sorting
II Exercises: 15
3. String Manipulations
4. Arrays
5. Functions
6. Sorting
Classes and Objects – Introspection – Serialization – Web Techniques:
Processing Forms – Setting Response Headers – Maintaining State :
Cookies and Session-Graphics
III Exercises: 15
7. Classes and Objects
8. Cookies and Sessions
9. Graphics
Working with MySQL Database: Select data from a single table –
Select data from multiple tables- Performing DML operations
IV Exercises: 15
10. Working with single table
11. Working with multiple tables
jQuery Fundamentals: Requirements of jQuery- JavaScript Premier –
jQuery Core – DOM Selection and Manipulation – Event Handling –
HTML Forms and Data – jQuery with PHP
V 15
Exercises:
12. Event Handling
13. Handling HTML Forms with jQuery
TOTAL 75
CO Course Outcomes
CO1 Demonstrate simple programs using PHP and jQuery

CO2 Apply the interface setup, styles & themes for the given application
Analyze the problem and add necessary user interface components, multimedia
CO3
components and web data source into the application
CO4 Evaluate the results by implementing the correct techniques on the web form
 CO5 Construct web applications with the facilitated components in PHP and jQuery

Textbooks
Kevin Tatroe, Peter MacIntyre, Rasmus Lerdorf, ― Programming PHP‖,

O‗Reilly Publications, Third Edition
 Joel Murach, Ray Harris (2010), ―PHP and MySQL‖, Shroff Publishers & Distributors

 Cesar Otero, Rob Lorsen (2012), ―Professional jQuery‖, John Wiley Sons & Inc

Reference Books
1. W. Jason Gilmore (2010), ―Beginning PHP & MySql‖, Apress

2. Larry Ullman (2008), ―PHP 6 and MySQL 5‖, Pearson Education

3. John Coggeshall (2006), ―PHP 5‖, Pearson Education

Michale C. Glass (2004), ―Beginning PHP, Apache, MySQL Web Development‖,

4.
Wiley DreamTech Press

Robin Nixon (2013), ―Learning PHP, MySQL, JavaScript & CSS‖, O‗Reilly, 2nd
5.
Edition

6. Jack Franlin (2013), ―Beginning jQuery‖, Apress, Springer Science

NOTE: Latest Edition of Textbooks May be Used

Web Resources
1. http://www.w3schools.com/jquery/

2. http://www.ccc.commnet.edu/faculty/sfreeman/cst%20250/jQueryNotes.pdf

3. http://www.w3schools.com/php/

4. http://www.tutorialspoint.com/php/

5. http://www.tutorialspoint.com/mysql/

CO/ PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 2 3 3 2
CO2 3 3 2 2 2 3
CO3 3 2 3 2 2 3
CO4 3 2 2 2 2 3
CO5 3 2 2 3 2 2
Weightage of course
contributed toeach PSO 15 11 11 12 11 13

SOFTWARE PROJECT MANAGEMENT

Subject Inst. Marks
L T P S Credits
Code Hours CIA External Total

4 0 0 - 4 4 25 75 100
Learning Objectives

LO1 To define and highlight importance of software project management.

To formulate and define the software management metrics & strategy in managing
LO2
projects
LO3 Understand to apply software testing techniques in commercial environment
Unit Contents No. of
Hours
Introduction to Competencies - Product Development Techniques - 12
I Management Skills - Product Development Life Cycle - Software
Development Process and models - The SEI CMM - International
Organization for Standardization.
Managing Domain Processes - Project Selection Models - Project 12
Portfolio Management - Financial Processes - Selecting a Project
II Team - Goal and Scope of the Software Project -Project Planning -
Creating the Work Breakdown Structure - Approaches to Building a
WBS - Project Milestones - Work Packages - Building a WBS for
Software.
Tasks and Activities - Software Size and Reuse Estimating - The 12
SEI CMM - Problems and Risks - Cost Estimation - Effort
III Measures - COCOMO: A Regression Model - COCOMO II -
SLIM: A Mathematical Model - Organizational Planning - Project
Roles and Skills Needed.
Project Management Resource Activities - Organizational Form and 12
Structure - Software Development Dependencies - Brainstorming -
IV Scheduling Fundamentals - PERT and CPM - Leveling Resource
Assignments - Map the Schedule to a Real Calendar - Critical Chain
Scheduling.
Quality: Requirements – The SEI CMM - Guidelines - Challenges -
Quality Function Deployment - Building the Software Quality
V Assurance - Plan - Software Configuration Management: Principles - 12
Requirements - Planning and Organizing - Tools - Benefits - Legal
Issues in Software - Case Study
TOTAL 60
CO Course Outcomes

CO1 Understand the principles and concepts of project management

CO2 Knowledge gained to train software project managers
 CO3 Apply software project management methodologies.

CO4 Able to create comprehensive project plans

CO5 Evaluate and mitigate risks associated with software development process
Textbooks
Robert T. Futrell, Donald F. Shafer, Linda I. Safer, ―Quality Software Project
 Management‖, Pearson Education Asia 2002.
Reference Books
1. Pankaj Jalote, ―Software Project Management in Practice‖, Addison Wesley 2002.

2. Hughes, ―Software Project Management‖, Tata McGraw Hill 2004, 3rd Edition.
NOTE: Latest Edition of Textbooks May be Used
Web Resources
1. NPTEL & MOOC courses titled Software Project Management

2. www.smartworld.com/notes/software-project-management

MAPPING TABLE

CO/ PSO PSO1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO1 3 2 1 2 2 2
CO2 3 1 3 2 2 2
CO3 2 3 2 3 3 3
CO4 3 3 2 3 3 2
CO5 2 2 2 3 3 3
Weightage of course
contributed
to eachPSO
13 11 10 13 13 12

SOFTWARE ENGINEERING

Subject Inst. Marks

L T P S Credits
Code Hours CIA External Total
5 0 0 V 3 5 25 75 100
Learning Objectives
LO1 This paper familiarizes the students about the processes, forms, tasks, techniques and
 tools involved in Software Engineering
LO2
To use the necessary for software engineering practice.
Prerequisites:
Unit Contents No. of
Hours
Introduction to Software Engineering: Definition - The changing nature
of software - Software Myths - Terminologies - Role of Management in
I Software Development - Software Life Cycle Models: The Waterfall 15
Model - Increment Process Model - Evolutionary Process Model - The
Unified Process.
Software Requirements Analysis and Specifications: Requirements
Engineering - Type of Requirements - Feasibility Studies - Requireents
II 15
Elicitation - Requirements Analysis - Requirements Documentation -
Requirements Validation.
Software Project Planning: Size Estimation - Cost Estimation - The
Constructive Cost Model (COCOMO) - COCOMO II - The Putnam
III Resource Allocation Model - Software Risk Management - Software 15
Design: Definition - Modularity - Strategy of Design - Function
Oriented Design.
Software Testing: A Strategic Approach to Software Testing -
IV Terminologies - Functional Testing - Structural Testing - Levels of 15
Testing - Validation Testing - Testing Tools.
Software Reliability: Basic Concepts - Software Quality - McCall
Software Quality Model - Boehm Software Quality Model - Capability
V 15
Maturity Model - Software Maintenance: Definition - Process - Models
- Configuration Management -Documentation.
TOTAL 75
THEORY & PROBLEM
CO Course Outcomes
Define the basic terminologies involved in the entire software developmental life
CO1
cycle
Identify suitable models, techniques and tools for the development of a software
CO2
product
Apply software engineering perspective through requirements analysis, software
CO3 design and construction, verification, and validation to develop solutions to modern
problems
CO4 Compare and contrast different process, cost, quality models and testing techniques
Estimate the project cost using suitable cost estimation models, rate the software risks
CO5
and evaluate management strategies for effective software development
Textbooks
 K.K Agarwal, Yogesh Singh (2009), ―Software Engineering‖, 3 rd Edition, New

Age International Publishers
Reference Books
Roger S. Pressman, ―Software Engineering – A Practioners Approach‖, 5 th Edition,
1.
Tata Mc Graw Hill Publication.
Panaj Jalote (2005), ―An Integrated Approach to Software Engineering‖, 3 rd
2.
Edition, Narosa Publication.
Thomas T. Baker, ―Writing Software Documentation – A task oriented approach‖,
3.
Second Edition, Pearson Education, 2004.
4. Rajib Mall, ―Fundamentals of Software Engineering‖, Second Edition, Prentice Hall.

NOTE: Latest Edition of Textbooks May be Used

Web Resources
1. http://www/tutorialspoint.com/software_engineering

2. http://www.nada.kth.se/lectures/

3. http://www2.latech.edu/

MAPPING TABLE

CO/ PSO PSO1 PSO2 PSO3 PSO4 PSO5 PSO6

CO1 3 2 3 2 2 2
CO2 2 3 3 3 3 2
CO3 2 2 3 3 3 3
CO4 3 2 2 3 3 3
CO5 3 3 3 3 3 3
Weightage ofcourse
contributed to each
PSO 13 12 14 14 14 13

SOFTWARE ENGINEERING LAB

Subject Inst. Marks

L T P S Credits
Code Hours CIA External Total
CC10 0 0 5 V 4 5 25 75 100
Learning Objectives

LO1 To Impart Practical Training in Software Engineering

LO2 To understand about different Software Testing
LO3 Learn to write test cases using different testing techniques.
 List of Exercises
Do the following 8 exercises for any project projects (Eg. Student Portal, Online exam
registration)
1) Development of problem statement.
2) Preparation of Software Requirement Specification Document.
3)Preparation of Software Configuration Management and Risk Management related documents.
4) Draw the entity relationship diagram
5) Draw the data flow diagrams at level 0 and level 1
6) Draw use case diagram
7) Draw activity diagram of all use cases.
8) Performing the Design by using any Design phase CASE tools.
9) Develop test cases for unit testing and integration testing
10) Develop test cases for various white box and black box testing techniques

TOTAL 75
CO Course Outcomes

CO1 An ability to use the methodology and tools necessary for engineering practice.

CO2 Ability to elicit, analyze and specify software requirements.

CO3 Analyze and translate specifications into a design.
CO4 Ability to derive test cases for different testing.
Apply software engineering perspective through requirements analysis, software design
CO5
and construction, verification, and validation to develop solutions to modern problems

MAPPING TABLE

CO/ PSO PSO1 PSO2 PSO3 PSO4 PSO5 PSO6

CO1 3 2 3 2 2 2
CO2 2 3 3 3 3 2
CO3 2 2 3 3 3 3
CO4 3 2 2 3 3 3
CO5 3 3 3 3 3 3
Weightage ofcourse
contributed to each
PSO 13 12 14 14 14 13

SOFTWARE METRICS

Subject L T P S Credits Inst. Marks

Code Hours CIA External Total

5 0 0 - 4 5 25 75 100
Learning Objectives
LO1 Gain a solid understanding of what software metrics are and their significance
LO2 Learn how to identify and select appropriate software metrics based on project goals
LO3 Acquire knowledge and skills in collecting and measuring software metrics
LO4 Learn how to analyze and interpret software metrics data to extract valuable insights
LO5 Gain the ability to evaluate software quality using appropriate metrics
Unit Contents No. of
Hours
Fundamentals of Measurement: Need for Measurement: Measurement 15
in Software Engineering, Scope of Software Metrics,
I The Basics of measurement: The representational theory of
measurement, Measurement and models, Measurement scales and
scale types, meaningfulness in measurement
A Goal-Based Framework For Software Measurement: Classifying 15
software measures, Determining what to Measure, Applying the
framework, Software measurement validation, Performing
II SoftwareMeasurementValidation
Empirical investigation: Principles of Empirical Studies, Planning
Experiments, Planning case studies as quasi-experiments, Relevant
and Meaningful Studies
Software Metrics Data Collection: Defining good data, Data collection 15
for incident reports, How to collect data, Reliability of data collection
Procedures
III
Analyzing software measurement data: Statistical distributions and
hypothesis testing, Classical data analysis techniques, Examples of
simple analysis techniques
Measuring internal product attributes: Size Properties of Software Size, 15
Code size, Design size, Requirements analysis and Specification size,
Functional size measures and estimators, Applications of size
IV measures
Measuring internal product attributes: Structure: Aspects of Structural
Measures, Control flow structure of program units, Design-
levelAttributes, Object-oriented Structural attributes and measures
Measuring External Product Attributes: Modelling software quality,
V Measuring aspects of quality, Usability Measures, Maintainability 15
measures,SecurityMeasures
 Software Reliability: Measurement and Prediction: Basics of reliability
theory, The software reliability problem, Parametric reliability growth
models, Predictive accuracy
TOTAL 75
CO Course Outcomes

CO1 Understand various fundamentals of measurement and software metrics

CO2 Identify frame work and analysis techniques for software measurement
CO3 Apply internal and external attributes of software product for effort estimation

CO4 Use appropriate analytical techniques to interpret software metrics data and derive
meaningful insights
CO5 Recommend reliability models for predicting software quality
Textbooks
Software Metrics A Rigorous and Practical Approach, Norman Fenton, James
 Bieman , Third Edition, 2014
Reference Books
Software metrics, Norman E, Fenton and Shari Lawrence Pfleeger, International
1
Thomson Computer Press, 1997
Metric and models in software quality engineering, Stephen H.Kan, Second edition,
2
2002, Addison Wesley Professional
Practical Software Metrics for Project Management and Process Improvement,
3
Robert B.Grady, 1992, Prentice Hall.
NOTE: Latest Edition of Textbooks May be Used
Web Resources
https://lansa.com/blog/general/what-are-software-metrics-how-can-i-measure-these-
1.
metrics/
2. https://stackify.com/track-software-metrics/

MAPPING TABLE

CO/ PSO PSO1 PSO2 PSO3 PSO4 PSO5 PSO6

CO1 3 2 2 2 2 2
CO2 2 3 3 3 3 2
CO3 2 2 3 3 3 3
CO4 3 2 2 3 2 3
CO5 3 3 3 2 3 3
 Weightage ofcourse
contributed to each
PSO 13 12 13 13 13 13

MACHINE LEARNING

Subject Inst. Marks

L T P S Credits
Code Hours CIA External Total

5 0 0 - 4 5 25 75 100
Learning Objectives
To comprehend the raw data and to design the same with the appropriate machine
LO1
learning algorithms for a meaningful representation of data..
Unit Contents No. of
Hours
Introduction: Machine Learning – Examples of Machine Learning 15
Applications. Supervised Learning: Learning a Class from Examples –
Vapnik-Chervonenkis (VC) Dimension – Probably Approximately
I Correct (PAC) Learning – Noise – Learning Multiple Classes –
Regression – Model Selection and Generalization – Dimensions of a
Supervised Machine Learning Algorithm. Bayesian Decision Theory:
Introduction – Classification – Losses and Risks – Discriminant
Functions – Association Rules.
Parametric Methods: Maximum Likelihood Estimation – Evaluating 15
an Estimator: Bias and Variance – The Bayes‘ Estimator – Parametric
Classification – Regression – Tuning Model Complexity: Bias/Variance
II Dilemma – Model Selection Procedures. Nonparametric Methods:
Nonparametric Density Estimation – Generalization to Multivariate
Data – Nonparametric Classification – Condensed Nearest Neighbor –
Distance-Based Classification – Outlier Detection – Nonparametric
Regression: Smoothing Models
Linear Discrimination – Generalizing the Linear Model – Geometry of 15
the Linear Discriminant – Pairwise Separation – Gradient Descent –
III Logistic Discrimination – Discrimination by Regression – Learning to
Rank. Multilayer Perceptrons: The Perceptron – Training a Perceptron
– Learning Boolean Functions – Multilayer Perceptrons – MLP as a
Universal Approximator – Backpropagation Algorithm
Combining Multiple Learners: Generating Diverse Learners – Model 15
IV Combination Schemes – Voting – Bagging – Boosting – Stacked
Generalization – Fine-Tuning an Ensemble – Cascading Reinforcement
 Learning: Elements of Reinforcement Learning – Model-Based
Learning – Temporal Difference Learning – Generalization – Partially
Observable States
Machine Learning with Python: Data Pre-processing, Analysis &
Visualization - Training Data and Test Data – Techniques – Algorithms:
List of Common Machine Learning Algorithms- Decision Tree
V Algorithm- Naïve Bayes Algorithm - K-Means-Random Forest- 15
Dimensionality Reduction Algorithm- Boosting Algorithms –
Applications: Social Media-Refinement of Search Engine Results-
Product Recommendations-Detection of Online frauds.
TOTAL 75
CO Course Outcomes

CO1 Outline the importance of machine learning in terms of designing intelligent machines

CO2 Identify suitable machine learning techniques for the real time applications

CO3 Analyze the theoretical concepts and how they relate to the practical aspects of machine
learning.
CO4 Assess the significance of principles, algorithms and applications of machine learning
through a hands-on approach
CO5 Compare the machine learning techniques with respective functionality
Textbooks
Ethem Alpaydın, ―Introduction to Machine Learning‖ Third Edition, MIT, 2014. (Unit
I – Unit IV)

https://www.tutorialspoint.com/machine_learning_with_python/machine_learning_wit
h_python_tutorial.pdf (Unit V: Machine learning with python tutorial)
Reference Books
1 1. Bertt Lantz, "Machine Learning with R," Packt Publishing, 2013

2 2. Jason Bell, "Machine Learning: Hands-On for Developers and Technical

Professionals," Wiley Publication, 2015.
3

NOTE: Latest Edition of Textbooks May be Used

Web Resources
1. https://www.expertsystem.com/machine-learning-definition/
. 2. https://searchenterpriseai.techtarget.com/definition/machine-learning-ML

MAPPING TABLE
CO/ PSO PSO1 PSO2 PSO3 PSO4 PSO5 PSO6

CO1 3 2 2 2 2 2
CO2 2 3 3 3 3 2
CO3 2 2 3 3 3 3
CO4 3 2 2 3 2 3
CO5 3 3 3 2 3 3
Weightage ofcourse
contributed to each
PSO 13 12 13 13 13 13
 NETWORK SECURITY
Marks

Inst. C Ex
Subject Code L T P S Credits Tot
Hours I ter
al
A nal

- 5 - - 4 5 25 75 100
Learning Objectives
LO1 To familiarize on the model of network security, Encryption techniques
LO2 To understand the design concept of cryptography and authentication
LO3 To develop experiments on algorithm used for security
LO4 To understand about virus and threats, firewalls, and implementation of Cryptography
UNIT Details No. of Hours
Model of network security – Security attacks, services and attacks –
OSI security architecture – Classical encryption techniques – SDES –
Block cipher PrinciplesDES – Strength of DES – Block cipher design
I 15
principles – Block cipher mode of operation – Evaluation criteria for
AES – RC4 - Differential and linear cryptanalysis – Placement of
encryption function – traffic confidentiality.
Number Theory – Prime number – Modular arithmetic – Euclid‘s
algorithm - Fermet‘s and Euler‘s theorem – Primality – Chinese
II remainder theorem – Discrete logarithm – Public key cryptography 15
and RSA – Key distribution – Key management – Diffie Hellman key
exchange – Elliptic curve cryptography
Authentication requirement – Authentication function – MAC – Hash
III function – Security of hash function and MAC – SHA - HMAC – 15
CMAC - Digital signature and authentication protocols – DSS.
Authentication applications – Kerberos – X.509 Authentication services
IV 15
- E- mail security – IP security - Web security
Intruder – Intrusion detection system – Virus and related threats –
V Countermeasures – Firewalls design principles – Trusted systems – 15
Practical implementation of cryptography and security
Total 75

Course Outcomes
Cours
e
On completion of this course, students will;
Outco
mes
Understand public-key cryptography, RSA and other public-key cryptosystems such as
CO1
Diffie-Hellman Key Exchange, ElGamal Cryptosystem.
CO2 Understand the security issues.
CO3 Apply key management and distribution schemes design. User Authentication
Analyze and design hash and MAC algorithms, and digital signatures. Analyze and
CO4
design classical encryption techniques and block ciphers.
CO5 Assess Intruders and Intruder Detection mechanisms, Types of Malicious software,
Reference Text :
William Stallings, ―Cryptography & Network Security‖, Pearson Education, Fourth
1.
Edition 2010.

References :

CharlieKaufman,RadiaPerlman,MikeSpeciner,―NetworkSecurity,Privatec
1.
ommunicationinpublicworld‖,PHISecondEdition,2002
Bruce Schneier, Neils Ferguson, ―Practical Cryptography‖, Wiley Dreamtech India
2.
Pvt Ltd, First Edition, 2003.
DouglasRSimson―Cryptography–
3.
Theoryandpractice‖,CRCPress,FirstEdition,1995
Web Resources
1. https://www.javatpoint.com/computer-network-security

2. https://www.tutorialspoint.com/information_security_cyber_law/network_security.htm

3. https://www.geeksforgeeks.org/network-security/

MAPPING TABLE

CO/ PSO PSO1 PSO2 PSO3 PSO4 PSO5 PSO6

CO1 3 2 2 2 2 2
CO2 2 3 3 3 3 2
CO3 2 2 3 3 3 3
CO4 3 2 2 3 2 3
CO5 3 3 3 2 3 3
Weightage ofcourse
contributed to each
PSO 13 12 13 13 13 13
 MOBILE APPLICATION DEVELOPMENT

Subject Inst. Marks

L T P S Credits
Code Hours CIA External Total

5 0 0 - 4 5 25 75 100
Learning Objectives
To provide the students with the basics of Android Software Development tools and
LO1
development of software on mobile platform.
Unit Contents No. of
Hours
Introduction to Android Operating System – Configuration 15
of Android Environment- Create the First Android
Application. Layout: Vertical, Vertical Scroll, horizontal,
I horizontal Scroll, Table Layout arrangement. Designing
User Interface: Label Text - TextView – Password Text
Box - Button –ImageButton – CheckBox – Image -
RadioButton – Slider – Autocomplete text View.

User Interface: Spinner – Switch – Side Bar- ListView - List Picker - 15

II Image Picker - Notifier - Time and Date Picker - Web Viewer

Media: Camcorder - Camera – Player – Speech 15

III Recognizer – Text to Speech – Video Player -
Canvas

Maps: Maps - Sensor: Location Sensor – Barcode Scanner 15

IV Social components: Contact Picker – Email Picker – Phone
Number Picker – Phone Call - Social: Texting

V Storage: Cloud DB – Tiny DB – Experimental – Fire DB 15

TOTAL 75
CO Course Outcomes

CO1 Chart the requirements needed for developing android application

CO2 Identify the results by executing the application in emulator or in android device
CO3 Apply proper interface setup, styles & themes, storing and management

CO4 Analyze the problem and add necessary user interface components, graphics and
multimedia components into the application.
 CO5 Evaluate the results by implementing the concept behind the problem with proper
code.
Textbooks
Karen Lang and Selim Tezel, (2022), Become an App Inventor The official

guide from MIT App Inventor, Miteen Press, Walker Books Limited.
Reference Books

1 Wei – Meng Lee, (2012), Beginning Android 4 Application Development,

Wiley India Edition.
2 Deital, Android for Programmers-An App-Driven Approach,Second Edition.

NOTE: Latest Edition of Textbooks May be Used

Web Resources
http://ai2.appinventor.mit.edu/reference/

. http://appinventor.mit.edu/explore/paint-pot-extended-camera
Subje Subject Name L T P S Marks

Category

Credits
ct

Extern

Total
Code

CIA

al
NATURAL Elect 4 - - 3 25 75 10
LANGUAGE 0
PROCESSING
Learning Objectives
LO1 To understand approaches to syntax and semantics in NLP.

LO2 To learn natural language processing and to learn how to apply basic algorithms in this
field.
To understand approaches to discourse, generation, dialogue and summarization within
LO3
NLP.
Toget acquainted with the algorithmic description of the main language levels:
LO4
morphology, syntax, semantics, pragmatics etc.
LO5 To understand current methods for statistical approaches to machine translation.
UNIT Contents No.
Of.
Hours
I Introduction : Natural Language Processing tasks in syntax, semantics, and
pragmatics – Issue- Applications – The role of machine learning – Probability
Basics –Information theory – Collocations -N-gram Language Models – 12
Estimating parameters and smoothing – Evaluating language models.
II Word level and Syntactic Analysis:Word Level Analysis: Regular
Expressions-Finite-State Automata-Morphological Parsing-Spelling Error
Detection and correction-Words and Word classes-Part-of Speech 12
Tagging.Syntactic Analysis: Context-free Grammar-Constituency- Parsing-
Probabilistic Parsing.
III Semantic analysis and Discourse Processing: Semantic Analysis: Meaning
Representation-Lexical Semantics- Ambiguity-Word Sense Disambiguation.
Discourse Processing: cohesion-Reference Resolution- Discourse Coherence 12
and Structure.
IV Natural Language Generation: Architecture of NLG Systems- Generation
Tasks and Representations- Application of NLG. Machine Translation:
Problems in Machine Translation. Characteristics of Indian Languages- 12
Machine Translation Approaches-Translation involving Indian Languages.
V Information retrieval and lexical resources: Information Retrieval: Design
features of Information Retrieval Systems-Classical, Non-classical, Alternative
Models of Information Retrieval – valuation Lexical Resources: WorldNet- 12
Frame NetStemmers- POS Tagger- Research Corpora SSAS.
Course Outcomes Programme
 Outcomes
CO On completion of this course, students will
Describe the fundamental concepts and techniques of natural language processing.
CO1 Explain the advantages and disadvantages of different NLP technologies and their
applicability in different business situations.
Distinguish among the various techniques, taking into account the assumptions,
strengths, and weaknesses of each
CO2
Use NLP technologies to explore and gain a broad understanding
of text data.
Use appropriate descriptions, visualizations, and statistics to communicate the
CO3 problems and their solutions.
Use NLP methods to analyse sentiment of a text document.
Analyze large volume text data generated from a range of real-world applications.
CO4
Use NLP methods to perform topic modelling.
Develop robotic process automation to manage business processes and to increase and
monitor their efficiency and effectiveness.
CO5
Determine the framework in which artificial intelligence and the Internet of things may
function, including interactions with people, enterprise functions, and environments.
Textbooks
1 Daniel Jurafsky, James H. Martin, ―Speech & language processing‖, Pearson
publications.
2 Allen, James. Natural language understanding. Pearson, 1995.

Reference Books
1. Pierre M. Nugues, ―An Introduction to Language Processing with Perl and
Prolog‖,Springer
Web Resources
1. https://en.wikipedia.org/wiki/Natural_language_processing

2. https://www.techtarget.com/searchenterpriseai/definition/natural-language-processing-
NLP
Mapping with Programme Outcomes:

CO/PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO 1 3 3 3 3 3 3
CO 2 2 3 3 3 2 3
3 3 3 3 3 3
CO 3
CO 4 3 2 3 3 2 3
 CO 5 3 3 3 3 3 3
Weightageof 14 14 15 15 13 15
coursecontributedtoeachPSO

ANALYTICS FOR SERVICE INDUSTRY

Subject Category L T P S Credits Marks
Code CIA External Total
Elect 4 - - - 3 25 75 100
Learning Objectives
LO1 Recognize challenges in dealing with data sets in service industry.

LO2 Identify and apply appropriate algorithms for analyzing the healthcare, Human
resource, hospitality and tourism data.
LO3 Make choices for a model for new machine learning tasks.
LO4 To identify employees with high attrition risk.
LO5 To Prioritizing various talent management initiatives for your organization.
UNIT No. Of. Hours
Contents
I Healthcare Analytics : Introduction to Healthcare Data
Analytics- Electronic Health Records– Components of EHR-
Coding Systems- Benefits of EHR- Barrier to Adopting HER
Challenges-Phenotyping Algorithms. Biomedical Image Analysis 12
and Signal Analysis- Genomic Data Analysis for Personalized
Medicine. Review of Clinical Prediction Models.
II Healthcare Analytics Applications : Applications and Practical
Systems for Healthcare– Data Analytics for Pervasive Health-
Fraud Detection in Healthcare- Data Analytics for Pharmaceutical
Discoveries- Clinical Decision Support Systems- Computer- 12
Assisted Medical Image Analysis Systems- Mobile Imaging and
Analytics for Biomedical Data.
III HR Analytics: Evolution of HR Analytics, HR information
systems and data sources, HR Metric and HR Analytics,
Evolution of HR Analytics; HR Metrics and HR Analytics; 12
Intuition versus analytical thinking; HRMS/HRIS and data
sources; Analytics frameworks like LAMP, HCM:21(r) Model.
IV Performance Analysis: Predicting employee performance,
Training requirements, evaluating training and development, 12
Optimizing selection and promotion decisions.
V Tourism and Hospitality Analytics: Guest Analytics – Loyalty
Analytics – Customer Satisfaction – Dynamic Pricing – optimized
disruption management – Fraud detection in payments. 12
 TOTAL HOURS 60
Course Outcomes Programme
Outcomes
CO On completion of this course, students will
Understand and critically apply the concepts and methods PO1, PO2, PO3, PO4,
CO1 of business analytics PO5, PO6

Identify, model and solve decision problems in different PO1, PO2, PO3, PO4,
CO2 settings. PO5, PO6

Interpret results/solutions and identify appropriate courses

CO3 of action for a given managerial situation whether a PO1, PO2, PO3, PO4,
problem or an opportunity. PO5, PO6

CO4 Create viable solutions to decision making problems. PO1, PO2, PO3, PO4,
PO5, PO6
Instill a sense of ethical decision-making and a
PO1, PO2, PO3, PO4,
CO5 commitment to the long-run welfare of both organizations
PO5, PO6
and the communities they serve.
Textbooks
1 Chandan K. Reddy and Charu C Aggarwal, ―Healthcare data analytics‖, Taylor &
Francis, 2015.
2 Edwards Martin R, Edwards Kirsten (2016),―Predictive HR Analytics: Mastering
the HR Metric‖, Kogan Page Publishers, ISBN-0749473924
3 Fitz-enzJac (2010), ―The new HR analytics: predicting the economic value of your
company‘s human capital investments‖, AMACOM, ISBN-13: 978-0-8144-1643-3
4 RajendraSahu, Manoj Dash and Anil Kumar. Applying Predictive Analytics Within
the Service Sector.
Reference Books
1. Hui Yang and Eva K. Lee, ―Healthcare Analytics: From Data to Knowledge to
Healthcare Improvement, Wiley, 2016
2. Fitz-enzJac, Mattox II John (2014), ―Predictive Analytics for Human Resources‖,
Wiley, ISBN- 1118940709.
Web Resources
1. https://www.ukessays.com/essays/marketing/contemporary-issues-in-marketing-
marketing-essay.php
2. https://yourbusiness.azcentral.com/examples-contemporary-issues-marketing-field-
26524.html

Mapping with Programme Outcomes:

CO/PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO 1 3 3 3 3 3 3
CO 2 2 3 3 3 3 3
CO 3 3 3 2 3 3 2
 CO 4 3 3 3 3 3 3
CO 5 3 3 3 3 3 3
Weightageof 14 15 14 15 15 14
coursecontributedtoeachPSO

S-Strong-3 M-Medium-2 L-Low-1

CRYPTOGRAPHY
Subject Category L T P S Credits Marks
Code CIA External Total
Elect 4 - - - 3 25 75 100
Learning Objectives
LO1 To understand the fundamentals of Cryptography
LO2 To acquire knowledge on standard algorithms used to provide confidentiality, integrity
and authenticity.
LO3 To understand the various key distribution and management schemes.
LO4 To understand how to deploy encryption techniques to secure data in transit across data
networks
LO5 To design security applications in the field of Information technology
UNIT Contents No. Of.
Hours
I Introduction: The OSI security Architecture – Security Attacks –
Security Mechanisms – Security Services – A model for network 12
Security.
II Classical Encryption Techniques: Symmetric cipher model –
Substitution Techniques: Caesar Cipher – Monoalphabetic cipher –
12
Play fair cipher – Poly Alphabetic Cipher – Transposition techniques –
Stenography
III Block Cipher and DES: Block Cipher Principles – DES – The
12
Strength of DES –RSA: The RSA algorithm.
IV Network Security Practices: IP Security overview - IP Security
architecture – Authentication Header. Web Security: SecureSocket 12
Layer and Transport Layer Security – Secure Electronic Transaction.
V Intruders – Malicious software – Firewalls. 12
TOTAL HOURS 60
Course Outcomes Programme
Outcomes
CO On completion of this course, students will
Analyze the vulnerabilities in any computing system and hence PO1, PO2, PO3,
CO1 be able to design a security solution. PO4, PO5, PO6

Apply the different cryptographic operations of symmetric PO1, PO2, PO3,

CO2 cryptographic algorithms PO4, PO5, PO6

Apply the different cryptographic operations of public key PO1, PO2, PO3,
CO3 cryptography PO4, PO5, PO6
 Apply the various Authentication schemes to simulate different PO1, PO2, PO3,
CO4 applications. PO4, PO5, PO6
Understand various Security practices and System security PO1, PO2, PO3,
CO5 standards PO4, PO5, PO6
Textbooks
1 William Stallings, ―Cryptography and Network Security Principles andPractices‖.

Reference Books
1. Behrouz A. Foruzan, ―Cryptography and Network Security‖, Tata McGraw-Hill,
2007.
2 AtulKahate, ―Cryptography and Network Security‖, Second Edition, 2003,TMH.
3 M.V. Arun Kumar, ―NetworkSecurity‖, 2011, First Edition,USP.
Web Resources
1 https://www.tutorialspoint.com/cryptography/
2 https://gpgtools.tenderapp.com/kb/how-to/introduction-to-cryptography
Mapping with Programme Outcomes:

CO/PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO 1 3 3 3 2 3 2
CO 2 3 2 3 2 3 3
CO 3 3 3 3 2 3 3
CO 4 2 3 3 3 2 3
CO 5 3 2 3 3 3 3
Weightage of course 14 13 15 12 14 14
contributed to each
PSO

BIG DATA ANALYTICS

Subject Category L T P S Credits Inst. Marks
Code Hours CIA External Total

Core 4 - - - 3 5 25 75 100

Course Objective
C1 Understand the Big Data Platform and its Use cases, Map Reduce Jobs
C2 To identify and understand the basics of cluster and decision tree
C3 To study about the Association Rules, Recommendation System
C4 To learn about the concept of stream
C5 Understand the concepts of NoSQL Databases
UNIT Details No. of
Hours
I Evolution of Big data — Best Practices for Big data Analytics — Big data
characteristics — Validating — The Promotion of the Value of Big Data
— Big Data Use Cases- Characteristics of Big Data Applications — 12
Perception and Quantification of Value -Understanding Big Data Storage
— A General Overview of High-Performance Architecture — HDFS —
MapReduce and YARN — Map Reduce Programming Model
II Advanced Analytical Theory and Methods: Overview of Clustering — K-
means — Use Cases — Overview of the Method — Determining the
Number of Clusters — Diagnostics — Reasons to Choose and Cautions .-
Classification: Decision Trees — Overview of a Decision Tree — The 12
General Algorithm — Decision Tree Algorithms — Evaluating a
Decision Tree — Decision Trees in R — Naïve Bayes — Bayes?
Theorem — Naïve Bayes Classifier.
III Advanced Analytical Theory and Methods: Association Rules —
Overview — Apriori Algorithm — Evaluation of Candidate Rules —
Applications of Association Rules — Finding Association& finding 12
similarity — Recommendation System: Collaborative Recommendation-
Content Based Recommendation — Knowledge Based Recommendation-
Hybrid Recommendation Approaches.
IV Introduction to Streams Concepts — Stream Data Model and Architecture
— Stream Computing,
Sampling Data in a Stream — Filtering Streams — Counting Distinct
Elements in a Stream — Estimating moments — Counting oneness in a 12
Window — Decaying Window — Real time Analytics Platform(RTAP)
applications — Case Studies — Real Time Sentiment Analysis, Stock
Market Predictions. Using Graph Analytics for Big Data: Graph Analytics
V NoSQL Databases : Schema-less Models?: Increasing Flexibility for Data
Manipulation-Key Value Stores- Document Stores — Tabular Stores —
Object Data Stores — Graph Databases Hive — Sharding —Hbase — 12
Analyzing big data with twitter — Big data for E-Commerce Big data for
blogs — Review of Basic Data Analytic Methods using R.

Total 60
Course Outcomes Programme Outcomes
CO On completion of this course, students will
1 Work with big data tools and its analysis techniques. PO1

2 Analyze data by utilizing clustering and classification

algorithms. PO1, PO2

3 Learn and apply different mining algorithms and PO4, PO6

 recommendation systems for large volumes of data.

4 Perform analytics on data streams. PO4, PO5, PO6

5 Learn NoSQL databases and management. PO3, PO8
Text Book

1 AnandRajaraman and Jeffrey David Ullman, ―Mining of Massive Datasets‖,

Cambridge University Press, 2012.
Reference Books

1. David Loshin, ―Big Data Analytics: From Strategic Planning to Enterprise

Integration with Tools, Techniques, NoSQL, and Graph‖, Morgan Kaufmann/El
sevier Publishers, 2013

2. EMC Education Services, ―Data Science and Big Data Analytics: Discovering,
Analyzing, Visualizing and Presenting Data‖, Wiley publishers, 2015.

Web Resources
1. https://www.simplilearn.com
2. https://www.sas.com/en_us/insights/analytics/big-data-analytics.html

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 M S

CO 3 S S

CO 4 S S M

CO 5 S S

S-Strong M-Medium L-Low

 INTERNET OF THINGS AND ITS APPLICATIONS

Subject Subject Name L T P S Marks

Inst. Hours
Category
Code

Credits

External

Total
CIA
Core Y - - - 3 4 2 75 100
5
Course Objective
C1 Use of Devices, Gateways and Data Management in IoT.
C2 Design IoT applications in different domain and be able to analyze their performance
C3 Implement basic IoT applications on embedded platform
C4 To gain knowledge on Industry Internet of Things
C5 To Learn about the privacy and Security issues in IoT
UNIT Details No. of Hours Course
Objectiv
e
I IoT & Web Technology, The Internet of Things Today,
Time for Convergence, Towards the IoT Universe,
Internet of Things Vision, IoT Strategic Research and
Innovation Directions, IoT Applications, Future
Internet Technologies, Infrastructure, Networks and 12 C1
Communication, Processes, Data Management,
Security, Privacy & Trust, Device Level Energy Issues,
IoT Related Standardization, Recommendations on
Research Topics.

II M2M to IoT – A Basic Perspective– Introduction,

Some Definitions, M2M Value Chains, IoT Value
Chains, An emerging industrial structure for IoT, The
international driven global value chain and global
12 C2
information monopolies. M2M to IoT-An Architectural
Overview– Building an architecture, Main design
principles and needed capabilities, An IoT architecture
outline, standards considerations.
III : IoT Architecture -State of the Art – Introduction,
State of the art, Architecture. Reference Model-
Introduction, Reference Model and architecture, IoT
reference Model, IoT Reference Architecture- 12 C3
Introduction, Functional View, Information View,
Deployment and Operational View, Other Relevant
architectural views

IV IoT Applications for Value Creations Introduction, IoT

applications for industry: Future Factory Concepts,
Brownfield IoT, Smart Objects, Smart Applications,
Four Aspects in your Business to Master IoT, Value 12 C4
Creation from Big Data and Serialization, IoT for
Retailing Industry, IoT For Oil and GasIndustry,
Opinions on IoT Application and Value for Industry,
Home Management
V Internet of Things Privacy, Security and Governance
Introduction, Overview of Governance, Privacy and
Security Issues, Contribution from FP7 Projects,
Security, Privacy and Trust in IoT-Data-Platforms for 12 C5
Smart Cities, First Steps Towards a Secure Platform,
Smartie Approach. Data Aggregation for the IoT in
Smart Cities, Security
Total 60
Course Outcomes Program
me
Outcomes
CO On completion of this course, students will
1 Work with big data tools and its analysis techniques. PO1

2 Analyze data by utilizing clustering and classification algorithms. PO1, PO2

3 Learn and apply different mining algorithms and recommendation

systems for large volumes of data. PO4, PO6

4 Perform analytics on data streams. PO4,

PO5, PO6
5 Learn NoSQL databases and management. PO3, PO8
Text Book
1 Vijay Madisetti and Arshdeep Bahga, ―Internet of Things: (A Hands-on Approach)‖,
 Universities Press (INDIA) Private Limited 2014, 1st Edition.

Reference Books
1. Michael Miller, ―The Internet of Things: How Smart TVs, Smart Cars, Smart Homes,
and Smart Cities Are Changing the World‖, kindle version.

2. Francis daCosta, ―Rethinking the Internet of Things: A Scalable Approach to

Connecting Everything‖, Apress Publications 2013, 1st Edition,.

3 WaltenegusDargie, ChristianPoellabauer, "Fundamentals of Wireless Sensor Networks:

Theory and Practice‖ 4..CunoPfister, ―Getting Started with the Internet of Things‖,
O‟Reilly Media 2011

Web Resources
1. https://www.simplilearn.com
2. https://www.javatpoint.com

3. https://www.w3schools.com

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 M S

CO 3 S S

CO 4 S S M

CO 5 S S

S-Strong M-Medium L-Low

H
C

Subject Subject Name L T P S Marks

n
d

u
a

g
o

o
e

r
e

r
I

s
t

t
t
i
.
Code

External

Total
CIA
Human Computer Elective
- Y - V 3 4 25 75 100
Interaction
Course Objective
C1 To learn about the foundations of Human Computer Interaction.
C2 To learn the design and software process technologies.
C3 To learn HCI models and theories.
C4 To learn Mobile Ecosystem.
C5 To learn the various types of Web Interface Design.

No. of
UNIT Details
Hours
FOUNDATIONS OF HCI :
 The Human: I/O channels – Memory
 Reasoning and problem solving; The Computer: Devices –
I 12
Memory – processing and networks;
 Interaction: Models – frameworks – Ergonomics – styles –
elements – interactivity- Paradigms. - Case Studies
II DESIGN & SOFTWARE PROCESS:

 Interactive Design:
 Basics – process – scenarios
 Navigation: screen design Iteration and prototyping. 12
 HCI in software process:
 Software life cycle – usability engineering – Prototyping in
practice – design rationale. Design rules: principles, standards,
guidelines, rules. Evaluation Techniques – Universal Design
III MODELS AND THEORIES:
 HCI Models : Cognitive models:- Socio-Organizational issues
12
and stakeholder requirements Communication and collaboration
models-Hypertext, Multimedia and WWW.
IV Mobile HCI:
 Mobile Ecosystem: Platforms, Application frameworks
 Types of Mobile Applications: Widgets, Applications, Games 12
 Mobile Information Architecture, Mobile 2.0,
 Mobile Design: Elements of Mobile Design, Tools. - Case Studies
V WEB INTERFACE DESIGN: Designing Web Interfaces – Drag &
Drop, Direct Selection, Contextual Tools, Overlays, Inlays and Virtual 12
Pages, Process Flow - Case Studies
 Total 60
Course Outcomes Programme Outcome
CO On completion of this course, students will
1 Understand the fundementals of HCI. PO1
Understand the design and software process
2 PO1, PO2
technologies.
3 Understand HCI models and theories. PO4, PO6
Understand Mobile Ecosystem, types of Mobile
4 PO4, PO5, PO6
Applications, mobile Architecture and design.
Understand the various types of Web Interface
5 PO3, PO8
Design.
Text Book
Alan Dix, Janet Finlay, Gregory Abowd, Russell Beale, ‖Human -Computer
1
Interaction‖‖, III Edition, Pearson Education, 2004 (UNIT I, II & III)
Brian Fling, ―‖Mobile Design and Development‖, I Edition, O‗Reilly Media Inc.,
2 2009(UNIT–IV)

Bill Scott and Theresa Neil, ―Designing Web Interfaces‖, First Edition, O‗Reilly, 2009.
3
(UNIT-V)
Reference Books
Shneiderman, ―Designing the User Interface: Strategies for Effective Human-Computer
1.
Interaction‖, V Edition, Pearson Education.
Web Resources
1. https://www.interaction-design.org/literature/topics/human-computer-interaction
2. https://link.springer.com/10.1007/978-0-387-39940-9_192
3. https://en.wikipedia.org/wiki/Human%E2%80%93computer_interaction
Mapping with Programme Outcomes:
PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8
CO 1 S
CO 2 S S

CO 3 S S

CO 4 S S S

CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks
Inst. Hours
Category

Code
Credits

External

Total
CIA

Fuzzy Logic Elective Y - - V 3 4 25 75 100

 Course Objective
CO1 To understand the basic concept of Fuzzy logic
CO2 To learn the various operations on relation properties
CO3 To study about the membership functions
CO4 To learn about the Defuzzification and Fuzzy Rule-Based System
CO5 To learn the concepts of Applications of Fuzzy Logic
UNIT Details No. of Course Objective
Hours
I Introduction to Fuzzy Logic- Fuzzy Sets- Fuzzy Set
12
Operations, Properties of Fuzzy Sets, Classical and C1
Fuzzy Relations: Introduction-Cartesian Product of
Relation-Classical Relations-Cardinality of Crisp
Relation.

II Operations on Crisp Relation-Properties of Crisp

Relations-Composition Fuzzy Relations, Cardinality of
Fuzzy Relations-Operations on Fuzzy Relations- 12
C2
Properties of Fuzzy Relations-Fuzzy Cartesian Product
and Composition-Tolerance and Equivalence Relations
,Crisp Relation.

III Membership Functions: Introduction, Features of

Membership Function, Classification of Fuzzy Sets,
Fuzzification, Membership Value Assignments, 12 C3

Intuition, Inference, Rank Ordering.

IV Defuzzification: Introduction, Lambda Cuts for Fuzzy

12
Sets, Lambda Cuts for Fuzzy Relations, Defuzzification C4
Methods, Fuzzy Rule-Based System: Introduction,
Formation of Rules, Decomposition of Rules,
Aggregation of Fuzzy Rules, Properties of Set of Rules.

V Applications of Fuzzy Logic: Fuzzy Logic in

 Automotive Applications, Fuzzy Antilock Brake
System-Antilock-Braking System and Vehicle Speed- 12 C5
Estimation Using Fuzzy Logic.

Total
Course Outcomes Programme Outcomes
CO On completion of this course, students will
1 Understand the basics of Fuzzy sets, operation and PO1
properties.
2 Apply Cartesian product and composition on Fuzzy
relations and usethe tolerance and Equivalence PO1, PO2
relations.

3 Analyze various fuzzification methods and features PO4, PO6

of membership Functions.
4 Evaluate defuzzification methods for real time PO4, PO5, PO6
applications.
5 Design an application using Fuzzy logic and its PO3, PO8
Relations.
Text Book
1
S. N. Sivanandam, S. Sumathi and S. N. Deepa-Introduction to Fuzzy Logic using
MATLAB, Springer-Verlag Berlin Heidelberg 2007.

Reference Books
1. Guanrong Chen and Trung Tat Pham- Introduction to Fuzzy Sets, Fuzzy Logic and
Fuzzy Control Systems

2. Timothy J Ross , Fuzzy Logic with Engineering Applications

Web Resources
1. https://www.javatpoint.com/fuzzy-logic

2. https://www.guru99.com/what-is-fuzzy-logic.html

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8
 CO 1 S

CO 2 M S

CO 3 S S

CO 4 S S M

CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours
Category
Code

Credits

External

Total
CIA
Artificial Intelligence Elective
- Y - - 3 4 25 75 100
Course Objective
C1 To learn various concepts of AI Techniques.
C2 To learn various Search Algorithm in AI.
C3 To learn probabilistic reasoning and models in AI.
C4 To learn about Markov Decision Process.
C5 To learn various type of Reinforcement learning.
No. of
UNIT Details
Hours
Introduction: Concept of AI, history, current status, scope, agents,

I environments, Problem Formulations, Review of tree and graph 12

structures, State space representation, Search graph and Search tree
II Search Algorithms : Random search, Search with closed and open list,
Depth first and Breadth first search, Heuristic search, Best first search, 12
A* algorithm, Game Search
III
Probabilistic Reasoning : Probability, conditional probability, Bayes
Rule, Bayesian Networks- representation, construction and inference, 12
temporal model, hidden Markov model.

IV Markov Decision process : MDP formulation, utility theory, utility

functions, value iteration, policy iteration and partially observable 12
MDPs.
 V Reinforcement Learning : Passive reinforcement learning, direct utility
estimation, adaptive dynamic programming, temporal difference 12
learning, active reinforcement learning- Q learning
Total 60
Course Outcomes Programme Outcome
CO On completion of this course, students will
1 Understand the various concepts of AI Techniques. PO1

2 Understand various Search Algorithm in AI. PO1, PO2

3 Understand probabilistic reasoning and models in PO4, PO6

AI.
4 Understand Markov Decision Process. PO4, PO5, PO6
Understand various type of Reinforcement learning PO3, PO8
5
Techniques.
Text Book
Stuart Russell and Peter Norvig, ―Artificial Intelligence: A Modern Approach‖ , 3rd
1 Edition, Prentice Hall.
Elaine Rich and Kevin Knight, ―Artificial Intelligence‖, Tata McGraw Hill
Reference Books
Trivedi, M.C., ―A Classical Approach to Artifical Intelligence‖, Khanna Publishing
1.
House, Delhi.
2. Saroj Kaushik, ―Artificial Intelligence‖, Cengage Learning India, 2011
David Poole and Alan Mackworth, ―Artificial Intelligence: Foundations for
3. Computational Agents‖, Cambridge University Press 2010
Web Resources
1. NPTEL&MOOCcoursestitledArtificialIntelligenceandExpertSystems
2. https://nptel.ac.in/courses/106106140/
3. https://nptel.ac.in/courses/106106126/

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 S S

CO 3 S S

CO 4 S S S
 CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours
Category
Code

Credits

External

Total
CIA
Robotics and Its Elective Y - - - 3 4 25 75 100
Applications
Course Objective
C1 To understand the robotics fundamentals
C2 Understand the sensors and matrix methods
C3 Understand the Localization: Self-localizations and mapping
C4 To study about the concept of Path Planning, Vision system
C5 To learn about the concept of robot artificial intelligence
UNIT Details No. of Course
Hours Objective
I Introduction: Introduction, brief history, components of
robotics, classification, workspace, work-envelop,
motion of robotic arm, end-effectors and its types,
12 CO1
service robot and its application, Artificial Intelligence
in Robotics.

II Actuators and sensors :Types of actuators, stepper-DC-

servo-and brushless motors- model of a DC servo
motor-types of transmissions-purpose of sensor-internal
and external sensor-common sensors-encoders
tachometers-strain gauge based force torque sensor- 12 CO2
proximity and distance measuring sensors

Kinematics of robots: Representation of joints and

frames, frames transformation, homogeneous matrix, D-
H matrix, Forward and inverse kinematics: two link
 planar (RR) and spherical robot (RRP). Mobile robot
Kinematics: Differential wheel mobile robot

III Localization: Self-localizations and mapping -

Challenges in localizations – IR based localizations –
vision based localizations – Ultrasonic based 12 CO3
localizations - GPS localization systems.

IV Path Planning: Introduction, path planning-overview-

road map path planning-cell decomposition path
planning potential field path planning-obstacle
avoidance-case studies

Vision system: Robotic vision systems-image 12 CO4

representation-object recognition-and categorization-

depth measurement- image data compression-visual
inspection-software considerations

V Application: Ariel robots-collision avoidance robots for

agriculture-mining-exploration-underwater-civilian- and
military applications-nuclear applications-space
Applications-Industrial robots-artificial intelligence in
12 CO5
robots-application of robots in material handling-
continuous arc welding-spot welding-spray painting-
assembly operation-cleaning-etc.

Total 60
Course Outcomes Programme Outcomes
CO On completion of this course, students will
1 Describe the different physical forms of robot
PO1
architectures.
2 Kinematically model simple manipulator and mobile
PO1, PO2
robots.
3 Mathematically describe a kinematic robot system PO4, PO6
 4 Analyze manipulation and navigation problems using
knowledge of coordinate frames, kinematics, PO4, PO5, PO6
optimization, control, and uncertainty.
5 Program robotics algorithms related to kinematics,
PO3, PO8
control, optimization, and uncertainty.
Text Book
1 RicharedD.Klafter. Thomas Achmielewski and MickaelNegin, Robotic Engineering
and Integrated Approach, Prentice Hall India-Newdelhi-2001

2 SaeedB.Nikku, Introduction to robotics, analysis, control and applications, Wiley-

India, 2 nd edition 2011
Reference Books
1. Industrial robotic technology-programming and application by M.P.Groover et.al,
McGrawhill2008
2. Robotics technology and flexible automation by S.R.Deb, THH-2009
Web Resources
1. https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_robotics.ht
m

2. https://www.geeksforgeeks.org/robotics-introduction/
Mapping with Programme Outcomes:
PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 M S

CO 3 S S

CO 4 S S M

CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours

Code
Category

Credits

External

Total
CIA

Computational Elective Y - - - 3 4 25 75 100

 Intelligence
Course Objective
C1 To identify and understand the basics of AI and its search.
C2 To study about the Fuzzy logic systems.
C3 Understand and apply the concepts of Neural Network and its functions.
C4 Understand the concepts of Artifical Neural Network
C5 To study about the Genetic Algorithm.
UNIT Details No. of Course Objective
Hours
I Introduction to AI: Problem formulation – AI
Applications – Problems – State Space and Search –
Production Systems – Breadth First and Depth First –
12 C1
Travelling Salesman Problem – Heuristic search
techniques: Generate and Test – Types of Hill
Climbing.

II Fuzzy Logic Systems:

Notion of fuzziness – Operations on fuzzy sets – T-
norms and other aggregation operators – Basics of
Approximate Reasoning – Compositional Rule of 12 C2
Inference – Fuzzy Rule Based Systems – Schemes
of Fuzzification – Inferencing – Defuzzification –
Fuzzy Clustering – fuzzy rule-based classifier.
III Neural Networks: What is Neural Network, Learning
rules and various activation functions, Single layer
Perceptions, Back Propagation networks, Architecture
of Backpropagation (BP) Networks, Back propagation
12 C3
Learning, Variation of Standard Back propagation
Neural Network, Introduction to Associative Memory,
Adaptive Resonance theory and Self Organizing Map,
Recent Applications
IV Artificial Neural Networks: Fundamental Concepts
– Basic Models of Artificial Neural Networks –
12 C4
Important Terminologies of ANNs – McCulloch-Pitts
Neuron – Linear Separability – Hebb Network.
V Genetic Algorithm: Introduction – Biological
Background – Genetic Algorithm Vs Traditional
Algorithm – Basic Terminologies in Genetic 12 C5
Algorithm – Simple GA – General Genetic
Algorithm – Operators in Genetic Algorithm
Total 60
 Course Outcomes Programme Outcomes
CO On completion of this course, students will
1 Describe the fundamentals of artificial intelligence
PO1
concepts and searching techniques.
2 Develop the fuzzy logic sets and membership
PO1, PO2
function and defuzzification techniques.
3 Understand the concepts of Neural Network and
PO4, PO6
analyze and apply the learning techniques
4 Understand the artificial neural networks and its
PO4, PO5, PO6
applications.
5 Understand the concept of Genetic Algorithm and
PO3, PO8
Analyze the optimization problems using GAs.
Text Book
1 S.N. Sivanandam and S.N. Deepa, ―Principles of Soft Computing‖, 2nd Edition, Wiley
India Pvt. Ltd.
2 Stuart Russell and Peter Norvig, ―Artificial Intelligence - A Modern Approach‖, 2nd
Edition, Pearson Education in Asia.
3 S. Rajasekaran, G. A. Vijayalakshmi, ―Neural Networks, Fuzzy Logic and Genetic
Algorithms: Synthesis & Applications‖, PHI.
Reference Books
1. F. Martin, Mc neill, and Ellen Thro, ―Fuzzy Logic: A Practical approach‖, AP
Professional, 2000. Chin Teng Lin, C. S. George Lee,‖ Neuro-Fuzzy Systems‖, PHI
2. Chin Teng Lin, C. S. George Lee,‖ Neuro-Fuzzy Systems‖, PHI.
Web Resources
1. https://www.javatpoint.com/artificial-intelligence-tutorial
2. https://www.w3schools.com/ai/
Mapping with Programme Outcomes:
PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S
CO 2 M S
CO 3 S S
CO 4 S S M
CO 5 S S
S-Strong M-Medium L-Low
H
C

Subjec Subject Name L T P S Marks

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d

u
a

g
o

o
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CIA
Grid Computing Elective
- Y - - 3 4 25 75 100
Course Objective
C1 To learn the basic construction and application of Grid computing.
C2 To learn grid computing organization and their Role.
C3 To learn Grid Computing Anotomy.
C4 To learn Grid Computing road map.
C5 To learn various type of Grid Architecture.
No. of
UNIT Details
Hours
Introduction: Early Grid Activity, Current Grid Activity, Overview of Grid
I Business areas, Grid Applications, Grid Infrastructures. 12

II Grid Computing organization and their Roles: Organizations Developing Grid

Standards, and Best Practice Guidelines, Global Grid Forum (GCF),
#Organization Developing Grid Computing Toolkits and Framework#, 12
Organization and building and using grid based solutions to solve computing,
commercial organization building and Grid Based solutions.
III Grid Computing Anatomy: The Grid Problem, The conceptual of virtual
organizations, # Grid Architecture # and relationship to other distributed 12
technology.
IV The Grid Computing Road Map: Autonomic computing, Business on demand
and infrastructure virtualization, Service-Oriented Architecture and Grid, 12
#Semantic Grids#.
V Merging the Grid services Architecture with the Web Services Architecture:
Service-Oriented Architecture, Web Service Architecture, #XML messages
and Enveloping#, Service message description Mechanisms, Relationship 12
between Web Services and Grid Services, Web services Interoperability and
the role of the WS-I Organization.
Total 60
Programme
Course Outcomes
Outcome
CO On completion of this course, students will
To understand the basic elements and concepts of Grid computing.
1 PO1

2 To understand the Grid computing toolkits and Framework. PO1, PO2

3 To understand the concepts of Anotomy of Grid Computing. PO4, PO6
4 To understand the concept of service oriented architecture. PO4, PO5, PO6
5 To Gain knowledge on grid and web service architecture. PO3, PO8
 Text Book
1 Joshy Joseph and Craig Fellenstein, Grid computing, Pearson / IBM Press, PTR, 2004.
Reference Books
1. Ahmer Abbas and Graig computing, A Practical Guide to technology and applications,
1.
Charles River Media, 2003.
Web Resources
1. https://en.wikipedia.org/wiki/Grid_computing
2. https://link.springer.com/chapter/10.1007/978-1-84882-409-6_4
3. https://www.redbooks.ibm.com/redbooks/pdfs/sg246778.pdf
Mapping with Programme Outcomes:
PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 S S

CO 3 S S

CO 4 S S S

CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours
Category

Code
Credits

External

Total
CIA

Trends in Computing Elective

- Y - - 3 4 25 75 100
Course Objective
C1 Learning current trends in various computer science and information technology fields.
C2 Learning various fields of Cloud computing, Green computing ,the Edge and Fog
computing technology.
C3 To learn about Architecture and Application design of Cloud, Edge & fog computing.
C4 To know computing and to improve security services of computing technologies.

C5 To learn the various Case Studies in Cloud, Edge & fog Computing.
UNIT Details No. of
 Hours
Era of Cloud Computing: Introduction – Components of Cloud
Computing – Cloud Types: Private, Public and Hybrid clouds –
I Limitations of the Cloud - Virtualization: Structure and Mechanisms. 12

II Cloud computing Services: Software as a Service(SaaS) – Platform as

a Service(PaaS)- Infrastructure as a Service(IaaS)-Database as a Service
(DBaaS)- Recent Trends in cloud computing and Standards-Data
Security in Cloud – Risks and Challenges with Cloud Data- Security as 12
a Service.

III
Edge Computing: Edge Computing and Its Essentials: Introduction-
Edge Computing Architecture- Advantages and Limitations of Edge
Computing Systems- Edge Computing Interfaces and Devices - Edge 12
Analytics: Edge Data Analytics – Potential of Edge Analytics –
Architecture of Edge Analytics – Case study

IV Edge Data storage Security: Edge-Based Attack Detection and

Prevention-Edge Computing Use Cases and Case Studies: Edge
Computing High- Potential Use Cases.
12
Introduction to green computing–Calculating carbon footprint-
Choosing Green PC path: A green make over – Buying green
computer- Choosing Earth Friendly peripherals
V Fog Computing: Introduction to Fog computing – Architecture -
Characteristics - Fog Computing Services – Fog Resource Estimation
12
and Its Challenges-Fog computing on 5G networks – Fog computing
Use cases and Case studies.
Total 60
Program
Course Outcomes me
Outcome
CO On completion of this course, students will

1 Outline the concepts, applications, benefits and limitations of various PO1

computing paradigms.

2 Classify the computing technologies based on its architecture and PO1, PO2
infrastructure and identify its strategies.

3 Examine various cloud services, Security threat exposure within a PO4, PO6
cloudcomputing infrastructure.
4 Asses the problems and solutions involved in various stages of different PO4,
 computing environments. PO5, PO6

5 Discuss the importance of cloud, edge and Fog technology and implement PO3, PO8
innovative ideas and practices for regulating green IT.
Text Book
Kailas Jayaswal,Jagannath Kallakurchi,Donald J.Houde,Dr.Devan Shah ― Cloud
1
Computing –Black Book‖ Edition :2020 (UNIT I & II : CHAPTER 1,2,3,9,11)
K. Anitha Kumari G. Sudha Sadasivam D. Dharani M. Niranjanamurthy, ―EDGE

2 COMPUTING Fundamentals, Advances and Applications‖, First Edition 2022, CRC

Press. ( UNIT III & IV : CHAPTER 1, 2 , 3, 4,5,6 )
Woody Leonhard and Katherine Murray (2009) ,Green Home Computing for
3
Dummies,Willey Publishing Inc. (UNIT IV : CHAPTER 2 ,5,6,7)
Evangelos Markakis, George Mastorakis, Constandinos X.Mavromoutakis and
4 Evangelos pallis ―Cloud and Fog computing in 5G mobile Networks‖ ,First edition
2017. ( UNIT V: CHAPTER 2 )
Reference Books
RajKumar Buyya, ChristianVecchiola, S.ThamaraiSelvi, (2013), Mastering Cloud
1.
Computing,McGraw Hill Education.

2. Michael Miller, (2009), Cloud Computing, Pearson Education.

Shijun Liu Bedir Tekinerdogan Mikio Aoyama Liang-Jie Zhang‖ Edge Computing –
3.
EDGE ― 2018.
FlavioBonomi, Rodolfo Milito, Jiang Zhu, SateeshAddepalli, ―Fog Computing and Its

4. Role in the Internet of Things‖, MCC‘12, August 17, 2012, Helsinki, Finland.
Copyright 2012.
Amir M. Rahmani · Pasi Liljeberg Jürgo-Sören Preden ―Fog Computing in the Internet
5
of Things‖Springer,2018. ( UNIT V: PART/CHAPTER (1.4,2.5)
Web Resources
1. https://static.googleusercontent.com/media/www.google.com/en//green/pdfs/google-
green- computing.pdf ( Case Study)
2. http://whatiscloud.com/basic_concepts_and_terminology/cloud
3. http://www.computerweekly.com/guides/Using-green-computing-for-improving-
energy- efficiency

Mapping with Programme Outcomes:

 PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 S S

CO 3 S S

CO 4 S S S

CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours
Category
Code

Credits

External

Total
CIA
Artificial Neural Core
- Y - - 3 4 25 75 100
Networks
Course Objective
C1 Understand the basics of artificial neural networks, learning process, single layer
and multi-layer perceptron networks.
C2 Understand the Error Correction and various learning algorithms and tasks.
C3 Identify the various Single Layer Perception Learning Algorithm.
C4 Identify the various Multi-Layer Perception Network.
C5 Analyze the Deep Learning of various Neural network and its Applications.
No. of
UNIT Details
Hours
Artificial Neural Model- Activation functions- Feed forward and
Feedback, Convex Sets, Convex Hull and Linear Separability, Non-

I Linear Separable Problem - Multilayer Networks. Learning Algorithms- 12

Error correction - Gradient Descent Rules, Perception Learning
Algorithm, Perception Convergence Theorem.
II Introduction, Error correction learning, Memory-based learning,
Hebbian learning, Competitive learning, Boltzmann learning, credit
15
assignment problem, Learning with and without teacher, learning tasks,
Memory and Adaptation.
III
.Single layer Perception: Introduction, Pattern Recognition, Linear
classifier, Simple perception, Perception learning algorithm, Modified
12
Perception learning algorithm, Adaptive linear combiner, Continuous
perception, Learning in continuous perception. Limitation of Perception.

IV Multi-Layer Perception Networks: Introduction, MLP with 2 hidden

layers, Simple layer of a MLP, Delta learning rule of the output layer,
12
Multilayer feed forward neural network with continuous perceptions,
Generalized delta learning rule, Back propagation algorithm
V Deep learning- Introduction- Neuro architectures building blocks for the
DL techniques, Deep Learning and Neocognitron, Deep Convolutional
Neural Networks, Recurrent Neural Networks (RNN), feature extraction, 12
Deep Belief Networks, Restricted Boltzman Machines, Training of DNN
and Applications
Total 60
Course Outcomes Programme Outcome
CO On completion of this course, students will
Students will learn the basics of artificial neural
1 networks with single layer and multi-layer PO1
perception networks.
Learn about the Error Correction and various
2 PO1, PO2
learning algorithms and tasks.
3 Learn the various Perception Learning Algorithm. PO4, PO6
Learn about the various Multi-Layer Perception
4 PO4, PO5, PO6
Network.
Understand the Deep Learning of various Neural
5 PO3, PO8
network and its Applications.
Text Book
Neural Networks A Classroom Approach- Satish Kumar, McGraw Hill- Second
1 Edition.
―Neural Network- A Comprehensive Foundation‖- Simon Haykins, Pearson Prentice
2. Hall, 2nd Edition, 1999.
Reference Books
1. Artificial Neural Networks-B. Yegnanarayana, PHI, New Delhi 1998.
Web Resources
 1. https://www.w3schools.com/ai/ai_neural_networks.asp
2. https://en.wikipedia.org/wiki/Artificial_neural_network
3. https://link.springer.com/chapter/10.1007/978-3-642-21004-4_12

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 S S

CO 3 S S

CO 4 S S S

CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours
Category

Code
Credits

External

Total
CIA

Agile Project Elective

- Y - - 3 4 25 75 100
Management
Course Objective
C1
Learning of software design, software technologies and APIs.
C2
Detailed demonstration about Agile development and testing techniques.
C3
Learning about Agile Planning and Execution.
C4
Learning of Agile Management Design and Quality Check.
C5
Detailed examination of Agile development and testing techniques.
No. of
UNIT Details
Hours
 Introduction:Modernizing Project Management: Project
Management Needed a Makeover – Introducing Agile Project
Management.

Applying the Agile Manifesto and Principles: Understanding the

Agile manifesto – Outlining the four values of the Agile manifesto –
I 12
Defining the 15 Agile Principles – Adding the Platinum Principles –
Changes as a result of Agile Values – The Agile litmus test.

Why Being Agile Works Better: Evaluating Agile benefits – How

Agile approaches beat historical approaches – Why people like being
Agile.
II
Being Agile

Agile Approaches: Diving under the umbrella of Agile approaches –

Reviewing the Big Three: Lean, Scrum, Extreme Programming -
Summary
12
Agile Environments in Action: Creating the physical environment –
Low-tech communicating – High-tech communicating – Choosing tools.

Agile Behaviours in Action: Establishing Agile roles – Establishing

new values – Changing team philosophy.
III Agile Planning and Execution
Defining the Product Vision and Roadmap: Agile planning –
Defining the product vision – Creating a product roadmap – Completing
the product backlog.
Planning Releases and Sprints: Refining requirements and estimates –
Release planning – Sprint planning.
Working Throughout the Day: Planning your day – Tracking progress
– Agile roles in the sprint – Creating shippable functionality – The end 12
of the day.
Showcasing Work, Inspecting and Adapting: The sprint review – The
sprint retrospective.
Preparing for Release: Preparing the product for deployment (the
release sprint) – Preparing the operational support – Preparing the
organization for product deployment - Preparing the marketplace for
product deployment
IV 12
Agile Management
 Managing Scope and Procurement: What‘s different about Agile
scope management – Managing Agile scope – What‘s different about
Agile procurement – Managing Agile procurement.
Managing Time and Cost: What‘s different about Agile time
management – Managing Agile schedules – What‘s different about
Agile cost management – Managing Agile budgets.
Managing Team Dynamics and Communication: What‘s different
about Agile team dynamics – Managing Agile team dynamics – What‘s
different about Agile communication – Managing Agile communication.
Managing Quality and Risk: What‘sdifferent about Agile quality –
Managing Agile quality – What‘s different about Agile risk management
– Managing Agile risk.
V
Implementing Agile
Building a Foundation: Organizational and individual commitment –
Choosing the right pilot team members – Creating and environment that
enables Agility – Support Agility initially and over time.
Being a Change Agent: Becoming Agile requires change – why change 12
doesn‘t happen on its own – Platinum Edge‘s Change Roadmap –
Avoiding pitfalls – Signs your changes are slipping.
Benefits, Factors for Success and Metrics: Ten key benefits of Agile
project management – Ten key factors for project success – Ten metrics
for Agile Organizations.
Total 60
Course Outcomes Programme Outcome
CO On completion of this course, students will

1 Understanding of software design, software PO1

technologies and APIs using Agile Management.

2 Understanding of Agile development and testing PO1, PO2

techniques.

3 Understanding about Agile Planning and Execution PO4, PO6

using Sprint.
Understanding of Agile Management Design, scope ,
4 Procurement, managing Time and Cost and Quality PO4, PO5, PO6
Check.

5 Analysing of Agile development and testing PO3, PO8

techniques.
Text Book
1 Mark C. Layton, Steven J. Ostermiller, Agile Project Management for Dummies, 2nd
 Edition, Wiley India Pvt. Ltd., 2018.
Jeff Sutherland, Scrum – The Art of Doing Twice the Work in Half the Time, Penguin,
2014.
Reference Books
Mark C. Layton, David Morrow, Scrum for Dummies, 2nd Edition, Wiley India Pvt.
1.
Ltd., 2018.
Mike Cohn, Succeeding with Agile – Software Development using Scrum,
2.
Addison-Wesley Signature Series, 2010.
3. Alex Moore, Agile Project Management, 2020.

4. Alex Moore, Scrum, 2020.

Andrew Stellman and Jennifer Greene, Learning Agile: Understanding Scrum, XP,
5. Lean, and Kanban, Shroff/O'Reilly, First Edition, 2014.
Web Resources
1. www.agilealliance.org/resources

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 S S

CO 3 S S

CO 4 S S S

CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours
Category
Code

Credits

External

Total
CIA
SEC1 OFFICE Specific -Y - - 2 2 25 75 100
AUTOMATION Elective
Course Objective
C1 Understand the basics of computer systems and its components.
C2 Understand and apply the basic concepts of a word processing package.
C3 Understand and apply the basic concepts of electronic spreadsheet software.
C4 Understand and apply the basic concepts of database management system.
C5 Understand and create a presentation using PowerPoint tool.
UNIT Details No. of
Hours
I Introductory concepts: Memory unit– CPU-Input Devices: Key board,
Mouse and Scanner. Output devices: Monitor, Printer. Introduction to
6
Operating systems & its features: DOS– UNIX–Windows. Introduction
to Programming Languages.
II Word Processing: Open, Save and close word document; Editing
text – tools, formatting, bullets; Spell Checker - Document
formatting – Paragraph alignment, indentation, headers and footers, 6
numbering; printing–Preview, options, merge.

III Spreadsheets : Excel–opening, entering text and data, formatting,

navigating; Formulas–entering, handling and copying; Charts–
creating, formatting and printing, analysis tables, preparation of 6
financial statements, introduction to data analytics.

IV Database Concepts: The concept of data base management system;

Data field, records, and files, Sorting and indexing data; Searching
records. Designing queries, and reports; Linking of datafiles;
6
Understanding Programming environment in DBMS; Developing
menu drive applications in query language (MS–Access).

V Power point: Introduction to Power point - Features –

Understanding slide typecasting & viewing slides – creating slide
shows. Applying special object – including objects & pictures – Slide 6
transition–Animation effects, audio inclusion, timers.

Total 30

Course Outcomes Programme Outcomes

CO On completion of this course, students will
1 Possess the knowledge on the basics of computers
PO1,PO2,PO3,PO6,PO8
and its components
 2 Gain knowledge on Creating Documents, spreadsheet
PO1,PO2,PO3,PO6
and presentation.
3 Learn the concepts of Database and implement the
PO3,PO5,PO7
Query in Database.
4 Demonstrate the understanding of different
PO3,PO4,PO5,PO7
automation tools.
5 Utilize the automation tools for documentation,
PO4,PO6,PO7,PO8
calculation and presentation purpose.
Text Book
1 Peter Norton,―Introduction to Computers‖–Tata Mc Graw-Hill.
Reference Books
1. Jennifer Ackerman Kettel, Guy Hat-Davis, Curt Simmons, ―Microsoft 2003‖, Tata
McGrawHill.
Web Resources
1. https://www.udemy.com/course/office-automation-certificate-course/
2. https://www.javatpoint.com/automation-tools
Mapping with Programme Outcomes:
PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 M S M M L
CO 2 S M S M
CO 3 S S M L
CO 4 S L M M
CO 5 M S M S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Categor

Credits

Code
Tota
y

Exte
CIA

rnal

BASICS OF INTERNET Specific 2 - - 2 25 75 100

SEC2 Elective
Learning Objectives
LO1 Knowledge of Internet medium
LO2 Internet as a mass medium
LO3 Features of Internet Technology,
LO4 Internet as source of infotainment
LO5 Study of internet audiences and about cyber crime
UNIT Contents No. Of.
Hours
I The emergence of internet as a mass medium – the world of ‗world wide
6
web‘.
II Features of internet as a technology. 6
III Internet as a source of infotainment – classification based on content and
6
style.
IV Demographic and psychographic descriptions of internet ‗audiences‘ –
6
effect of internet onthe values and life-styles.
V Present issues such as cyber crime and future possibilities. 6
TOTAL HOURS 30

CO Course Outcomes
 Knows the basic concept in HTML
CO1 Concept of resources in HTML

Knows Design concept.

CO2 Concept of Meta Data
Understand the concept of save the files.
Understand the page formatting.
CO3 Concept of list
Creating Links.
CO4 Know the concept of creating link to email address
Concept of adding images
CO5 Understand the table creation.

Textbooks
1 ―Mastering HTML5 and CSS3 Made Easy‖, TeachUComp Inc., 2014.
2
Thomas Michaud, “Foundations of Web Design: Introduction to HTML & CSS”

Web Resources
1. https://www.teachucomp.com/samples/html/5/manuals/Mastering-HTML5-CSS3.pdf

2. https://www.w3schools.com/html/default.asp

Subject Subject Name L T P S Marks

Inst. Hours
Category

Code
Credits

External

Total
CIA
 PROBLEM SOLVING Specific
Y - - - 2 2 25 75 100
TECHNIQUES Elective
Course Objective
C1 Understand the systematic approach to problem solving.

C2 Know the approach and algorithms to solve specific fundamental problems.

C3 Understand the efficient approach to solve specific factoring-related problems.

C4 Understand the efficient array-related techniques to solve specific problems.

Understand the efficient methods to solve specific problems related to text processing.
C5
Understand how recursion works.
UNIT Details No. of
Hours
I 6
Introduction: Notion of algorithms and programs – Requirements for
solving problems by computer – The problem-solving aspect: Problem
definition phase, Getting started on a problem, The use of specific
examples, Similarities among problems, Working backwards from the
solution – General problem-solving strategies - Problem solving using top-
down design – Implementation of algorithms – The concept of Recursion.
II 6
Fundamental Algorithms: Exchanging the values of two variables –
Counting - Summation of a set of numbers - Factorial computation - Sine
function computation - Fibonacci Series generation - Reversing the digits
of an integer – Base Conversion.
III 6
Factoring Methods: Finding the square root of a number – The smallest
divisor of an integer – Greatest common divisor of two integers -
Generating prime numbers – Computing the prime factors of an integer –
Generation of pseudo-random numbers - Raising a number to a large
power – Computing the nth Fibonacci number.

IV 6
Array Techniques: Array order reversal – Array counting or
histograming – Finding the maximum number in a set - Removal of
duplicates from an ordered array - Partitioning an array – Finding the kth
smallest element – Longest monotone subsequence.
V 6
Text Processing and Pattern Searching: Text line length adjustment –
Left and right justification of text – Keyword searching in text – Text line
editing – Linear pattern search.
Recursive algorithms: Towers of Hanoi – Permutation generation.

Total 30
 Course Outcomes Programme Outcome
CO On completion of this course, students will
1 Understand the logic of problem and analyses
implementation of algorithm and TopDown PO1,PO6
approach and concept of Recursion
2 Able to understand the Sequence of Numbers and
PO2
Series Fibonacci, Reversing ,Base Conversion.
3 Able to do Algebraic operations PO2,PO4
4 Coverage of Arrays and its Logics PO6,PO8
5 Text Processing and Pattern Searching Approach PO7
Text Book
1 R. G. Dromey, How to Solve it by Computer, Pearson India, 2007

Reference Books
1.
George Polya, Jeremy Kilpatrick, The Stanford Mathematics Problem Book: With
Hints and Solutions, Dover Publications, 2009 (Kindle Edition 2013).

2.
Greg W. Scragg, Problem Solving with Computers, Jones & Bartlett 1st edition, 1996.

Web Resources
1. https://www.studytonight.com/

2. https://www.w3schools.com/

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 M S

CO 2 M

CO 3 S L

CO 4 S M

CO 5 M

S-Strong M-Medium L-Low

Multimedia Lab

Subject Inst. Marks

L T P S Credits
Code Hours CIA External Total
SEC4 0 0 2 III 1 2 25 75 100
Learning Objectives
LO1 Understands the basics of multimedia
LO2 Acquire knowledge of image editing and animation techniques.
LO3 Apply multimedia concepts to real world projects
Unit Contents No. of
Hours
GIMP‘s Tools- Taking Advantage of Paths - Working with Layers and 6
masks - Using Channels
Exercises:
I 1. Enlarge a Logo using path
2. Create an ink drawing using path
3. Replace Background of image using Channels

Manipulating Images: Transforming Images - Using The Image Tools - 6

Adjusting Colors - Working with Text - Painting in Gimp: Creating
new brushes - Enhancing Photos - Exploring Filters and Effects.
Exercises:
II 1. Design Front Cover for a Book.
2. Create a customized logo
3. Use clone tool to remove text from an image
4. Remove Red eye using Filter.

Using GIMP animation package - Managing the Frames of Image 6

Sequence with GAP - Morphing - onion skinning - Creating a
Storyboard.
III
Exercises:
1. Morphing - Create smooth transitions from one image to
another.
2. Create a Story board for your project
Flash: Introduction - Creating and Editing Objects - Color and Text. 6
Animations: Frame- by- frame animation-Motion Tweening- Motion
Guides
IV 1. Creating Frame-by-frame Animation
2. Create a Motion Tween for Graphic and Text Object
3. Create a Motion guide Layer

Shape Tweening - Masking - Interactivity: Adding Script to

Buttons - Testing and Publishing.
V Exercises: 6
1. Create a Shape Tween for Graphic Object
2. Create a Mask Layer
3. Adding buttons with Action Script
 TOTAL 30
CO Course Outcomes

CO1 Demonstrate understanding and use of multimedia fundamentals

Implement appropriate techniques required for editing images and designing

CO2
animated system

CO3 Solve various design and implementation issues materialize on the development
of multimedia systems
CO4 Assess different Photo Editing, Video Editing and animation tools and select the
appropriate tool based on the requirements
CO5 Design and develop Multimedia Projects
Textbooks
1. Jason Van Gumster& Robert Shimonski (2010), ―GIMP Bible‖, Wiley, 2nd
edition.

2. Chris Gover, 2010, ―Flash CS5: The missing Manual‖, 1st Edition, O‟ Reilly
India.
Reference Books
1 Juan Manuel Ferreyra (2011), ―GIMP 2.6 Cookbook‖, PACK publishing Ltd.

2Robert Reinhard (2003), ―Macromedia Flash MX Bible‖, Wiley Dreamtech India

Pvt Ltd.
NOTE: Latest Edition of Textbooks May be Used
Web Resources
1. https://www.youtube.com/watch?v=T8NIK3RdoIc (Unit IV: Gimp Video Editing)
2. https://www.youtube.com/watch?v=Jz9WrbELGYA

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 M S M M L
CO 2 S M S M
CO 3 S S M L
CO 4 S L M M
CO 5 M S M S
 Subject Subject Name L T P S Marks

Category

Credits
Code

Exter

Total
CIA

nal
FUNDAMENTALS OF Specific 2 - - I 2 25 75 100
INFORMATION Elective
TECHNOLOGY
Learning Objectives
LO1 Understand basic concepts and terminology of information technology.
LO2 Have a basic understanding of personal computers and their operation
LO3 Be able to identify data storage and its usage
LO4 Get great knowledge of software and its functionalities
LO5 Understand about operating system and their uses
UNIT Contents No. Of.
Hours
I Introduction to Computers:
Introduction, Definition, .Characteristics of computer, Evolution
of Computer, Block Diagram Of a computer, Generations of 6
Computer, Classification Of Computers, Applications of
Computer, Capabilities and limitations of computer
II Basic Computer Organization:
Role of I/O devices in a computer system. Input Units: Keyboard,
Terminals and its types. Pointing Devices, Scanners and its types,
Voice Recognition Systems, Vision Input System, Touch Screen, 6
Output Units: Monitors and its types. Printers: Impact Printers
and its types. Non Impact Printers and its types, Plotters, types of
plotters, Sound cards, Speakers.
III Storage Fundamentals:
Primary Vs Secondary Storage, Data storage & retrieval methods.
Primary Storage: RAM ROM, PROM, EPROM, EEPROM.
Secondary Storage: Magnetic Tapes, Magnetic Disks. Cartridge 6
tape, hard disks, Floppy disks Optical Disks, Compact Disks, Zip
Drive, Flash Drives

IV Software:
Software and its needs, Types of S/W. System Software:
Operating System, Utility Programs Programming Language:
Machine Language, Assembly Language, High Level Language 6
their advantages & disadvantages. Application S/W and its types:
Word Processing, Spread Sheets Presentation, Graphics, DBMS
s/w
V Operating System:
Functions, Measuring System Performance, Assemblers,
Compilers and Interpreters.Batch Processing, Multiprogramming, 6
Multi Tasking, Multiprocessing, Time Sharing, DOS, Windows,
 Unix/Linux.

TOTAL HOURS 30
Course Outcomes Programme
Outcomes
CO On completion of this course, students will
 Learn the basics of computer, Construct the structure of the required PO1, PO2,
CO1 things in computer, learn how to use it. PO3, PO4,
PO5, PO6

 Develop organizational structure using for the devices present PO1, PO2,
CO2 currently under input or output unit. PO3, PO4,
PO5, PO6

Concept of storing data in computer using two header namely RAM PO1, PO2,
CO3 and ROM with different types of ROM with advancement in PO3, PO4,
storage basis. PO5, PO6

CO4
 Work with different software, Write program in the software and PO1, PO2,
applications of software. PO3, PO4,
PO5, PO6
Usage of Operating system in information technology which really PO1, PO2,
CO5 acts as a interpreter between software and hardware. PO3, PO4,
PO5, PO6
Textbooks
1 Anoop Mathew, S. Kavitha Murugeshan (2009), ― Fundamental of Information
Technology‖, Majestic Books.
2 Alexis Leon, Mathews Leon,‖ Fundamental of Information Technology‖, 2nd Edition.
3 S. K Bansal, ―Fundamental of Information Technology‖.
Reference Books
1. Bhardwaj Sushil Puneet Kumar, ―Fundamental of Information Technology‖
2. GG WILKINSON, ―Fundamentals of Information Technology‖, Wiley-Blackwell
3. A Ravichandran , ―Fundamentals of Information Technology‖, Khanna Book
Publishing
Web Resources
1. https://testbook.com/learn/computer-fundamentals
2. https://www.tutorialsmate.com/2020/04/computer-fundamentals-tutorial.html
3. https://www.javatpoint.com/computer-fundamentals-tutorial
4. https://www.tutorialspoint.com/computer_fundamentals/index.htm
5. https://www.nios.ac.in/media/documents/sec229new/Lesson1.pdf

Mapping with Programme Outcomes:

 CO/PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO 1 3 3 3 3 3 3
CO 2 3 3 3 3 3 3
CO 3 3 3 3 3 3 3
CO 4 3 3 3 3 2 3
CO 5 3 3 2 3 3 2
Weightage of course 15 15 14 15 14 14
contributed to each
PSO

S-Strong-3 M-Medium-2 L-Low-1

Subject Subject Name L T P S Marks

Category

Credits
Code

Exter

Total
CIA

nal
INTRODUCTION TO Specific 2 - - 2 25 75 100
HTML Elective
Learning Objectives
LO1 Insert a graphic within a web page.
LO2 Create a link within a web page.
LO3 Create a table within a web page.
LO4 Insert heading levels within a web page.
LO5 Insert ordered and unordered lists within a web page. Create a web page.
UNIT Contents No. Of.
Hours
I Introduction :Web Basics: What is Internet – Web browsers – What is
6
Web page – HTML Basics: Understanding tags.
II Tags for Document structure( HTML, Head, Body Tag). Block level
text elements: Headings paragraph(<p> tag) – Font style elements: (bold, 6
italic, font, small, strong, strike, big tags)
III Lists: Types of lists: Ordered, Unordered – Nesting Lists – Other tags:
6
Marquee, HR, BR- Using Images – Creating Hyperlinks.
IV Tables: Creating basic Table, Table elements, Caption – Table and cell
6
alignment – Rowspan, Colspan – Cell padding.
V Frames: Frameset – Targeted Links – No frame – Forms : Input, Textarea,
Select, Option. 6
TOTAL HOURS 30

Course Outcomes Programme

Outcomes
CO On completion of this course, students will
  Knows the basic concept in HTML PO1, PO2, PO3,
CO1 Concept of resources in HTML PO4, PO5, PO6
Knows Design concept. PO1, PO2, PO3,
CO2 Concept of Meta Data PO4, PO5, PO6
Understand the concept of save the files.
Understand the page formatting. PO1, PO2, PO3,
CO3 Concept of list PO4, PO5, PO6
Creating Links. PO1, PO2, PO3,
CO4 Know the concept of creating link to email address PO4, PO5, PO6
Concept of adding images PO1, PO2, PO3,
CO5 Understand the table creation. PO4, PO5, PO6

Textbooks
1 ―Mastering HTML5 and CSS3 Made Easy‖, TeachUComp Inc., 2014.
2
Thomas Michaud, “Foundations of Web Design: Introduction to HTML & CSS”

Web Resources
1. https://www.teachucomp.com/samples/html/5/manuals/Mastering-HTML5-CSS3.pdf

2. https://www.w3schools.com/html/default.asp

Mapping with Programme Outcomes:

CO/PSO PSO 1 PSO 2 PSO 3 PSO 4 PSO 5 PSO 6

CO 1 3 3 3 3 3 3
CO 2 3 3 2 3 3 3
CO 3 2 3 3 3 3 3
CO 4 3 3 3 3 3 3
CO 5 3 3 3 2 3 3

Weightage of course 14 15 14 14 15 15
contributed to each
PSO
S-Strong-3 M-Medium-2 L-Low-1

Subject Subject Name L T P S Marks

Categor

Credits

Hours

Code
Inst.

Exter

Total
y

CIA

nal

WEB DESIGNING Specific Y - - - 2 2 25 75 100

Elective
Course Objective
C1 Understand the basics of HTML and its components

C2 To study about the Graphics in HTML

C3 Understand and apply the concepts of XML and DHTML

C4 Understand the concept of JavaScript

C5 To identify and understand the goals and objectives of the Ajax

UNIT Details No. of Course
Hour Objective
s
I HTML: HTML-Introduction-tag basics- page structure-adding
comments working with texts, paragraphs and line break.
Emphasizing test- heading and horizontal rules-list-font size,
6 C1
face and color-alignment links-tables-frames.
II Forms & Images Using Html: Graphics: Introduction-How to
work efficiently with images in web pages, image maps, GIF
animation, adding multimedia, data collection with html forms
textbox, password, list box, combo box, text area, tools for
6 C2
building web page front page.
III XML & DHTML: Cascading style sheet (CSS)-what is CSS-
Why we use CSS-adding CSS to your web pages-Grouping
styles-extensible markup language (XML). 6 C3
IV Dynamic HTML: Document object model (DCOM)-
Accessing HTML & CSS through DCOM Dynamic content
styles & positioning-Event bubbling-data binding.
JavaScript: Client-side scripting, What is JavaScript, How to
develop JavaScript, simple JavaScript, variables, functions, 6 C4
conditions, loops and repetition,
V Advance script, JavaScript and objects, JavaScript own 6
objects, the DOM and web browser environments, forms and C5
validations.
Total 60
Course Outcomes Programme Outcome
CO On completion of this course, students will
1 Develop working knowledge of HTML PO1, PO3, PO6, PO8
2 Ability to Develop and publish Web pages using
PO1,PO2,PO3,PO6
Hypertext Markup Language (HTML).
3 Ability to optimize page styles and layout with
PO3, PO5
Cascading Style Sheets (CSS).
4 Ability to develop a java script PO1, PO2, PO3, PO7
5 An ability to develop web application using Ajax. P02, PO6, PO7
Text Book
1 Pankaj Sharma, ―Web Technology‖, SkKataria& Sons Bangalore 2011.
 2 Mike Mcgrath, ―Java Script‖, Dream Tech Press 2006, 1st Edition.
3 Achyut S Godbole&AtulKahate, ―Web Technologies‖, 2002, 2nd Edition.
Reference Books
1. Laura Lemay, RafeColburn , Jennifer Kyrnin, ―Mastering HTML, CSS &Javascript
Web Publishing‖, 2016.
2. DT Editorial Services (Author), ―HTML 5 Black Book (Covers CSS3, JavaScript,
XML, XHTML, AJAX, PHP, jQuery)‖, Paperback 2016, 2nd Edition.
Web Resources
1. NPTEL & MOOC courses titled Web Design and Development.
2. https://www.geeksforgeeks.org

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S M L M

CO 2 S M L M

CO 3 S M

CO 4 S M M L

CO 5 M L M

S-Strong M-Medium L-Low

Subjec Subject Name L T P S Marks

Inst. Hours
Category

t Code
Credits

External

Total
CIA

SoftwareTesting Specific Y - - - 2 2 25 75 100

Elective
Course Objective
C1 To study fundamental concepts in software testing
C2 To discuss various software testing issues and solutions in software unit test,
integration and system testing.
C3 To study the basic concept of Data flow testing and Domain testing.
C4 To Acquire knowledge on path products and path expressions.
 C5 To learn about Logic based testing and decision tables
UNIT Details No. of Hours Course
Objective
I Introduction: Purpose–Productivity and Quality in
Software–TestingVsDebugging–Model for Testing– 6
Bugs–Types of Bugs – Testing and Design Style. C1

II Flow / Graphs and Path Testing – Achievable

paths – Path instrumentation Application
Transaction FlowTesting Techniques. 6 C2

III Data Flow Testing Strategies - Domain

Testing:Domains and Paths – Domains and 6
Interface Testing. C3

IV Linguistic –Metrics – Structural Metric – Path

Products and Path Expressions.SyntaxTesting– 6
Formats–Test Cases C4

V Logic Based Testing–Decision Tables–

Transition Testing–States, State Graph, 6
C5
StateTesting.
Total 30

Course Outcomes Program Outcomes

CO On completion of this course, students will
1 Students learn to apply software testing knowledge
PO1
and engineering methods
2 Have an ability to identify the needs of software test
automation, and define and develop a test tool to PO1, PO2
support test automation.
3 Have an ability understand and identify various
software testing problems, and solve these problems
PO4, PO6
by designing and selecting software test models,
criteria, strategies, and methods.
4 Have basic understanding and knowledge
of contemporary issues in software testing, such as PO4, PO5, PO6
component-based software testing problems
5 Have an ability to use software testing methods and
modern software testing tools for their testing PO3, PO8
projects.
Text Book
1 B.Beizer,―SoftwareTestingTechniques‖,IIEdn.,DreamTechIndia,NewDelhi,
2003.
 2 K.V.K.Prasad,―SoftwareTestingTools‖,DreamTech.India,NewDelhi,2005
Reference Books
1. I.Burnstein,2003,―PracticalSoftwareTesting‖,SpringerInternationalEdn.
2. E. Kit, 1995, ―Software Testing in the Real World: Improving the
Process‖,
PearsonEducation,Delhi.
3. R. Rajani,andP.P.Oak,2004,―SoftwareTesting‖,TataMcgrawHill,New
Delhi.
Web Resources
1. https://www.javatpoint.com/software-testing-tutorial

2. https://www.guru99.com/software-testing.html

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 M S

CO 3 S S

CO 4 S S M

CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours
Category

Code
Credits

External

Total
CIA

Quantitative Aptitude Specific Y - - - 2 2 25

75 100
Elective
Course Objective
C1 To understand the basic concepts of numbers
C2 Understand and apply the concept of percentage, profit & loss
C3 To study the basic concepts of time and work, interests
C4 To learn the concepts of permutation, probability, discounts
C5 To study about the concepts of data representation, graphs
UNIT Details No. of Course
 Hours Objective
I Numbers-HCF and LCM of numbers-Decimal
fractions-Simplification-Squareroot and cuberoots - 6 CO1
Average-problems on Numbers.
II Problems on Ages - Surds and Indices - percentage -
profits and loss - ratio and proportion-partnership- 6 CO2
Chainrule.
III Time and work - pipes and cisterns - Time and
Distance - problems on trains -Boats and streams -
simple interest - compound interest - Logarithms - 6 CO3
Area-Volume and surfacearea -races and
Gamesofskill.
IV Permutation and combination-probability-True
Discount-Bankers Discount – Height and Distances- 6 CO4
Oddmanout & Series.
V Calendar - Clocks - stocks and shares - Data
representation - Tabulation - BarGraphs-Piecharts- 6 CO5
Linegraphs.

Total 60
Course Outcomes Programme Outcome
CO On completion of this course, students will
1 understand the concepts, application and the problems of
PO1
numbers
2 To have basic knowledge and understanding about
PO1, PO2
percentage, profit & loss related processings
3 To understand the concepts of time and work PO4, PO6
4 Speaks about the concepts of probability, discount PO4, PO5, PO6
5 Understanding the concept of problem solving involved in
PO3, PO8
stocks & shares, graphs
Text Book
1 ―QuantitativeAptitude‖,R.S.AGGARWAL.,S.Chand&CompanyLtd.,
Reference Books
1.
Web Resources
1. https://www.javatpoint.com/aptitude/quantitative

2. https://www.toppr.com/guides/quantitative-aptitude/
Mapping with Programme Outcomes:
PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 M S

CO 3 S S

CO 4 S S M

CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours
Code Category

Credits

External

Total
CIA
Multimedia Systems Specific Y - - - 2 2 25 75 100
Elective
Course Objective
C1 Understand the basics of Multimedia
C2 To study about the Image File Formats,Sounds Audio File Formats
C3 Understand the concepts of Animation and DigitalVideoContainers
C4 To study about the Stage of Multimedia Project
C5 Understand the concept of
OwnershipofContentCreatedforProjectAcquiringTalent
UNIT Details No. of Course
Hours Objective
I Multimedia Definition-Use Of Multimedia-
Delivering Multimedia- Text:About Fonts and 12
C1
Faces - Using Text in Multimedia -Computers
and Text Font Editing and DesignTools-
HypermediaandHypertext.
II Images: Plan Approach - Organize Tools -
Configure Computer Workspace -Making Still
Images - Color - Image File Formats. Sound:
12
The Power of Sound -DigitalAudio-MidiAudio- C2
Midivs.DigitalAudio-MultimediaSystemSounds
Audio File Formats -Vaughan's Law of
Multimedia Minimums - Adding
SoundtoMultimediaProject
 III Animation:The Power of Motion-Principles of
Animation-Animation by Computer - Making
Animations that Work. Video: Using Video -
12 C3
Working with Video and Displays-
DigitalVideoContainers-ObtainingVideo Clips
-ShootingandEditingVideo
IV Making Multimedia: The Stage of Multimedia Project
- The Intangible Needs -The Hardware Needs - The 12
C4
Software Needs - An Authoring Systems Needs-
MultimediaProductionTeam.
V PlanningandCosting:TheProcessofMakingMulti
media-Scheduling-Estimating - RFPs and Bid
Proposals. Designing and Producing - Content
12
andTalent:AcquiringContent- C5
OwnershipofContentCreatedforProject-
AcquiringTalent
Total 60
Course Outcomes Programme Outcomes
CO On completion of this course, students will
1 understand the concepts, importance, application and
PO1
the process of developing multimedia
2 to have basic knowledge and understanding about
PO1, PO2
image related processings
3 To understand the framework of frames and bit
PO4, PO6
images to animations
4 Speaks about the multimedia projects and stages of
PO4, PO5, PO6
requirement in phases of project.
5 Understanding the concept of cost involved in
PO3, PO8
multimedia planning, designing, and producing
Text Book
1 TayVaughan,"Multimedia:MakingItWork",8thEdition,Osborne/McGraw-
Hill,2001.
Reference Books
1. RalfSteinmetz&KlaraNahrstedt"MultimediaComputing,Communication&
Applications",PearsonEducation,2012.
Web Resources
1. https://www.geeksforgeeks.org/multimedia-systems-with-features-or-characteristics/

Mapping with Programme Outcomes:

 PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 M S

CO 3 S S

CO 4 S S M

CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours
Category
Code

Credits

External

Total
CIA
Specific Y - - - 2 2 25 75 100
Advanced Excel Elective
Course Objective
C1 Handle large amounts of data
C2 Aggregate numeric data and summarize into categories and subcategories
C3 Filtering, sorting, and grouping data or subsets of data
C4 Create pivot tables to consolidate data from multiple files
C5 Presenting data in the form of charts and graphs
UNIT Details No. of Course Objective
Hours
I
Basics of Excel- Customizing common options-
Absolute and relative cells- Protecting and un-
protecting worksheets and cells- Working with
Functions - Writing conditional expressions - logical
functions - lookup and reference functions- VlookUP
6 C1
with Exact Match, Approximate Match- Nested
VlookUP with Exact Match- VlookUP with Tables,
Dynamic Ranges- Nested VlookUP with Exact Match-
Using VLookUP to consolidate Data from Multiple
Sheets

II Data Validations - Specifying a valid range of values - 6 C2

 Specifying a list of valid values- Specifying custom
validations based on formula - Working with
Templates Designing the structure of a template-
templates for standardization of worksheets - Sorting
and Filtering Data -Sorting tables- multiple-level
sorting- custom sorting- Filtering data for selected
view - advanced filter options- Working with Reports
Creating subtotals- Multiple-level subtotal.
III Creating Pivot tables Formatting and customizing
Pivot tables- advanced options of Pivot tables- Pivot
charts- Consolidating data from multiple sheets and
files using Pivot tables- external data sources- data
6 C3
consolidation feature to consolidate data- Show Value
As % of Row, % of Column, Running Total, Compare
with Specific Field- Viewing Subtotal under Pivot-
Creating Slicers.
IV
More Functions Date and time functions- Text
functions- Database functions- Power Functions -
Formatting Using auto formatting option for
6 C4
worksheets- Using conditional formatting option for
rows, columns and cells- WhatIf Analysis - Goal
Seek- Data Tables- Scenario Manager.

V Charts - Formatting Charts- 3D Graphs- Bar and Line

Chart together- Secondary Axis in Graphs- Sharing
Charts with PowerPoint / MS Word, Dynamically- 6 C5
New Features Of Excel Sparklines, Inline Charts, data
Charts- Overview of all the new features.
Total 30
Course Outcomes Programme Outcomes
CO On completion of this course, students will
1 Work with big data tools and its analysis techniques. PO1

2 Analyze data by utilizing clustering and classification

algorithms. PO1, PO2

3 Learn and apply different mining algorithms and

recommendation systems for large volumes of data. PO4, PO6

4 Perform analytics on data streams. PO4, PO5, PO6

5 Learn NoSQL databases and management. PO3, PO8
Text Book
 1 Excel 2019 All
2 Microsoft Excel 2019 Pivot Table Data Crunching
Web Resources
1. https://www.simplilearn.com
2 https://www.javatpoint.com

3 https://www.w3schools.com

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CO 1 S

CO 2 M S

CO 3 S S

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CO 5 S S

S-Strong M-Medium L-Low

Inst. Hours Marks

Category

Credits

Externa
Subject Code Subject Name L T P S

Total
CIA

l
Biometrics Specific Y - - - 2 2 25
75 100
Elective
Course Objectives

CO1 Identify the various biometric technologies.

CO2 Design of biometric recognition.

CO3 Develop simple applications for privacy

CO4 Understand the need of biometric in the society

CO5 Understand the scope of biometric techniques

No. of Course
UNIT Details
Hours Objectives
 Introduction: What is Biometrics, History,Types of
biometric Traits, General architecture of biometric
systems, Basic working of biometric matching,
Biometric system error and performance measures,
Design of biometric system, Applications of
biometrics, Biometrics versus traditional
I authentication methods. 6 CO1
Face Biometrics: Introduction, Background of Face
Recognition, Design of Face Recognition System,
Neural Network for Face Recognition, Face Detection
in Video Sequences, Challenges in Face Biometrics,
.7 Face Recognition Methods, Advantages and
Disadvantages.
Retina and Iris Biometrics: Introduction,
Performance of Biometrics, Design of Retina
Biometrics, Design of Iris Recognition System, Iris
Segmentation Method , Determination of Iris Region,
Determination of Iris Region, Applications of Iris
II Biometrics, Advantages and Disadvantages 6 CO2
Vein and Fingerprint Biometrics: Introduction,
Biometrics Using Vein Pattern of Palm, Fingerprint
Biometrics, Fingerprint Recognition System, Minutiae
Extraction, Fingerprint Indexing, Experimental
Results, Advantages and Disadvantages.
Privacy Enhancement Using Biometrics:
Introduction, Privacy Concerns Associated with
Biometric Deployments, Identity and Privacy, Privacy
Concerns, Biometrics with Privacy Enhancement,
Comparison of Various Biometrics in Terms of
Privacy, Soft Biometrics.
III 6 CO3
Multimodal Biometrics: Introduction to Multimodal
Biometrics , Basic Architecture of Multimodal
Biometrics, Multimodal Biometrics Using Face and
Ear, Characteristics and Advantages of Multimodal
Biometrics, Characteristics and Advantages of
Multimodal Biometrics.
WatermarkingTechniques: Introduction, Data
Hiding Methods, Basic Framework of Watermarking,
IV Classification of Watermarking, Applications of 6 CO4
Watermarking, Attacks on Watermarks, Performance
Evaluation, Characteristics of Watermarks, General
Watermarking Process, Image Watermarking
 Techniques, Watermarking Algorithm, Experimental
Results, Effect of Attacks on Watermarking
Techniques, Attacks on Spatial Domain
Watermarking.
Scope and Future: Scope and Future Market of
Biometrics, Biometric Technologies, Applications of
Biometrics, Biometrics and Information Technology
Infrastructure, Role of Biometrics in Enterprise
Security, Role of Biometrics in Border Security,
Smart Card Technology and Biometrics, Radio
Frequency Identification (RFID) Biometrics, DNA
V Biometrics, Comparative Study of Various Biometric 6 CO5
Techniques.
Biometric Standards: Introduction, Standard
Development Organizations, Application
Programming Interface (API), Information Security
and Biometric Standards, Biometric Template
Interoperability.
Total 30
Course Outcomes

Course
On completion of this course, students will;
Outcomes
To understand the basic concepts and the functionality
CO1 of the Biometrics, Face Biometrics, Types, PO1, PO3, PO6, PO8
Architecture and Applications.
CO2 To know the concepts Retina and Iris Biometrics and PO1,PO2,PO3,PO6
Vein and Fingerprint Biometrics.
To analyse the Privacy Enhancement and Multimodal
CO3 PO3, PO5
Biometrics.
CO4 To get analyticalidea on Watrmarking Techniques PO1, PO2, PO3, PO7
To Gain knowledge on Future scope of
CO5 Biometrics,and Study of various Biometric PO2, PO6, PO7
Techniques.
Recommended Text
Biometrics: Concepts and Applications by G.R Sinha and SandeepB.Patil ,
1.
Wiley, 2013
References Books
Guide to Biometrics by Ruud M. Bolle , SharathPankanti, Nalinik.Ratha,
1.
Andrew W.Senior, Jonathan H. Connell , Springer 2009
 2. Introduction to Biometrics by Anil k. Jain, Arun A. Ross, KarthikNandakumar
3. Hand book of Biometrics by Anil K. Jain, Patrick Flynn, ArunA.Ross.
Web Resources
1. https://www.tutorialspoint.com/biometrics/index.htm
2. https://www.javatpoint.com/biometrics-tutorial
https://www.thalesgroup.com/en/markets/digital-identity-and-
3.
security/government/inspired/biometrics

Mapping with Programme Outcomes:

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CO 1 S M L M

CO 2 S M L M

CO 3 S M

CO 4 S M M L

CO 5 M L M

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours
Code
Category

Credits

External

Total
CIA
Cyber Forensics Specific Y - - - 2 2 25 75 100
Elective
Course Objective
C1 Understand the definition of computer forensics fundamentals.
C2 To study about the Types of Computer Forensics Evidence
C3 Understand and apply the concepts of Duplication and Preservation of Digital Evidence
C4 Understand the concepts of Electronic Evidence and Identification of Data
C5 To study about the Digital Detective, Network Forensics Scenario, Damaging
Computer Evidence.
UNIT Details No. of Hours Course
Objective
I Overview of Computer Forensics Technology:
Computer Forensics Fundamentals: What is
C1
Computer Forensics? Use of Computer Forensics in
Law Enforcement, Computer Forensics Assistance to
 Human Resources/Employment Proceedings,
Computer Forensics Services, Benefits of 6
professional Forensics Methodology, Steps taken by
Computer Forensics Specialists. Types of Computer.
Forensics Technology: Types of Business Computer
Forensic, Technology–Types of Military Computer
Forensic Technology–Types of Law Enforcement–
Computer Forensic. Technology–Types of Business
Computer Forensic Technology.
II Computer Forensics Evidence and capture: Data 6
Recovery: Data Recovery Defined, Data Back–up
and Recovery, The Role of Back –up in Data
Recovery, The Data –Recovery Solution. Evidence
Collection and Data Seizure: Collection Options,
C2
Obstacles, Types of Evidence, The Rules of
Evidence, Volatile Evidence, General Procedure,
Collection and Archiving, Methods of Collections,
Artefacts, Collection Steps, Controlling
Contamination: The chain of custody.
III Duplication and Preservation of Digital Evidence:
Processing steps, Legal Aspects of collecting and
Preserving Computer forensic Evidence. Computer
C3
image Verification and Authentication: Special needs 6
of Evidential Authentication, Practical Consideration,
Practical Implementation.

IV Computer Forensics Analysis: Discovery of

Electronic Evidence: Electronic Document
Discovery: A Powerful New Litigation Tool.
C4
Identification of Data: Time Travel, Forensic 6
Identification and Analysis of Technical Surveillance
Devices.
V Reconstructing Past Events: How to Become a
C5
 Digital Detective, Useable File Formats, Unusable
File Formats, Converting Files. Networks: Network 6
Forensics Scenario, a technical approach, Destruction
Of E–Mail, Damaging Computer Evidence,
Documenting The Intrusion on Destruction of Data,
System Testing.
Total 30
Course Outcomes Programme Outcomes
CO On completion of this course, students will
1 Understand the definition of computer forensics
PO1
fundamentals.

2 Evaluate the different types of computer forensics

PO1, PO2
technology.

3 Analyze various computer forensics systems. PO4, PO6

4 Apply the methods for data recovery, evidence

PO4, PO5, PO6
collection and data seizure.

5 Gain your knowledge of duplication and preservation

PO3, PO8
of digital evidence.

Text Book
1 John R. Vacca, ―Computer Forensics: Computer Crime Investigation‖, 3/E ,Firewall
Media, New Delhi, 2002.
Reference Books
1. Nelson, Phillips Enfinger, Steuart,―Computer Forensics and Investigations‖ Enfinger,
Steuart, CENGAGE Learning, 2004.
2. Anthony Sammes and Brian Jenkinson,‖Forensic Computing: A Practitioner&#39;s
Guide‖, Second Edition, Springer–Verlag London Limited, 2007.
3. .Robert M.Slade,‖ Software Forensics Collecting Evidence from the Scene of a Digital
Crime‖, TMH 2005.
Web Resources
1. https://www.vskills.in

2. https://www.hackingarticles.in/best-of-computer-forensics-tutorials/
Mapping with Programme Outcomes:
PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8

CO 1 S

CO 2 M S

CO 3 S S

CO 4 S S M

CO 5 S S

S-Strong M-Medium L-Low

Subject Subject Name L T P S Marks

Inst. Hours
Code Category

Credits

External

Total
CIA
Pattern Recognition Specific Y - - - 2 2 75 25 100
Elective
Course Objective
CO1 To learn the fundamentals of Pattern Recognition techniques
CO2 To learn the various Statistical Pattern recognition techniques
CO3 To learn the linear discriminant functions and unsupervised learning and clustering
CO4 To learn the various Syntactical Pattern recognition techniques
CO5 To learn the Neural Pattern recognition techniques
UNIT Details No. of Course Objective
Hours
I PATTERN RECOGNITION OVERVIEW: Pattern
recognition, Classification and Description-Patterns and
6 CO1
feature Extraction with Examples-Training and
Learning in PR systems-Pattern recognition Approaches
II STATISTICAL PATTERN RECOGNITION:
Introduction to statistical Pattern Recognition-
6 CO2
supervised Learning using Parametric and Non-
Parametric Approaches.
III LINEAR DISCRIMINANT FUNCTIONS AND
UNSUPERVISED LEARNING AND CLUSTERING:
Introduction-Discrete and binary Classification 6 CO3
Problems-Techniques to directly Obtain linear
Classifiers - Formulation of Unsupervised Learning
Problems-Clustering for unsupervised learning and
 classification
IV SYNTACTIC PATTERN RECOGNITION: Overview
of Syntactic Pattern Recognition-Syntactic recognition
via parsing and other grammars–Graphical Approaches 6 CO4
to syntactic pattern recognition-Learning via
grammatical inference.
V NEURAL PATTERN RECOGNITION: Introduction to
Neural Networks-Feedforward Networks and training
6 CO5
by Back Propagation-Content Addressable Memory
Approaches and Unsupervised Learning in Neural PR
Total
Course Outcomes Programme Outcomes
CO On completion of this course, students will
1 understand the concepts, importance, application and the
PO1
process of developing Pattern recognition over view
2 to have basic knowledge and understanding about parametric
PO1, PO2
and non-parametric related concepts.
3 To understand the framework of frames and bit images to
PO4, PO6
animations
4 Speaks about the multimedia projects and stages of
PO4, PO5, PO6
requirement in phases of project.
5 Understanding the concept of cost involved in multimedia
PO3, PO8
planning, designing, and producing
Text Book
1 Robert Schalkoff, ―Pattern Recognition: Statistical Structural and Neural Approaches‖,
John wiley & sons.
2 Duda R.O., P.E.Hart & D.G Stork, ― Pattern Classification‖, 2nd Edition, J.Wiley.
3 Duda R.O.& Hart P.E., ―Pattern Classification and Scene Analysis‖, J.wiley.
4 Bishop C.M., ―Neural Networks for Pattern Recognition‖, Oxford University Press.
Reference Books
1. 1. Earl Gose, Richard johnsonbaugh, Steve Jost, ―Pattern Recognition and Image
Analysis‖, Prentice Hall of India, Pvt Ltd, New Delhi.
Web Resources
1. https://www.geeksforgeeks.org/pattern-recognition-introduction/
2. https://www.mygreatlearning.com/blog/pattern-recognition-machine-learning/

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8
 CO 1 S

CO 2 M S

CO 3 S S

CO 4 S S M

CO 5 S S

S-Strong M-Medium L-Low

Marks

Inst. Hours
Category

Credits

External
Subject Code Subject Name L T P S

Total
CIA
Enterprise Resource Specific Y - - - 4 4 25
Planning Elective 75 100

Course Objectives
CO1 To understand the basic concepts, Evolution and Benefits of ERP.
CO2 To know the need and Role of ERP in logical and Physical Integration.
Identify the important business functions provided by typical business
CO3 software such as enterprise resource planning and customer relationship
managemen
To train the students to develop the basic understanding of how ERP enriches
CO4
the business organizations in achieving a multidimensional growth
To aim at preparing the students technological competitive and make them
CO5
ready to self-upgrade with the higher technical skills
No. of
UNIT Details
Hours
ERP Introduction, Benefits, Origin, Evolution and Structure:
Conceptual Model of ERP, the Evolution of ERP, the Structure of
I 6
ERP, Components and needs of ERP, ERP Vendors; Benefits &
Limitations of ERP Packages.
Need to focus on Enterprise Integration/ERP; Information mapping;
Role of common shared Enterprise database; System Integration,
II Logical vs. Physical System Integration, Benefits & limitations of 6
System Integration, ERP‘s Role in Logical and Physical Integration.
Business Process Reengineering, Data ware Housing, Data Mining,
Online Analytic Processing (OLAP), Product Life Cycle Man-
 agement (PLM), LAP, Supply chain Management.
ERP Marketplace and Marketplace Dynamics: Market Overview,
Marketplace Dynamics, the Changing ERP Market. ERP- Functional
Modules: Introduction, Functional Modules of ERP Software,
III 6
Integration of ERP, Supply chain and Customer Relationship
Applications. Cloud and Open Source, Management, Material
Management, Financial Module, CRM and Case Study.
ERP Implementation Basics, , ERP implementation Strategy, ERP
Implementation Life Cycle ,Pre- Implementation task,Role of
IV 6
SDLC/SSAD, Object Oriented Architecture, Consultants, Vendors
and Employees.
ERP & E-Commerce, Future Directives- in ERP, ERP and Internet,
Critical success and failure factors, Integrating ERP into or-
V 6
ganizational culture. Using ERP tool: either SAP or ORACLE
format to case study.

Total 30

Course Outcomes
Course
On completion of this course, students will;
Outcomes
CO1 Understand the basic concepts of ERP.
CO2 Identify different technologies used in ERP
Understand and apply the concepts of ERP Manufacturing Perspective and ERP
CO3
Modules
CO4 Discuss the benefits of ERP
CO5 Apply different tools used in ERP
Reference Text :
1. Enterprise Resource Planning – Alexis Leon, Tata McGraw Hill.
References :
1. Enterprise Resource Planning – Diversified by Alexis Leon, TMH.
2. Enterprise Resource Planning – Ravi Shankar & S. Jaiswal , Galgotia
Web Resources
1. https://www.tutorialspoint.com/management_concepts/enterprise_resour
1.
ce_planning.htm
1. https://www.saponlinetutorials.com/what-is-erp-systems-enterprise-
2.
resource-planning/
3. 1. https://www.guru99.com/erp-full-form.html
4. 2. https://www.oracle.com/in/erp/what-is-erp/

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6
 CO 1 M L M
CO 2 M S L M
CO 3 L M
CO 4 M L
CO 5 M L M
S-Strong M-Medium L-Low
Subjec Subject Name L T P S Marks

Inst. Hours
Category
t Code

Credits

External

Total
CIA
Robotics and Its Applications Specific Y - - - 2 2 25 75 100
Elective
Course Objective
C1 To understand the robotics fundamentals
C2 Understand the sensors and matrix methods
C3 Understand the Localization: Self-localizations and mapping
C4 To study about the concept of Path Planning, Vision system
C5 To learn about the concept of robot artificial intelligence
UNIT Details No. of Course
Hours Objective
I Introduction: Introduction, brief history, components of robotics,
classification, workspace, work-envelop, motion of robotic arm, end-
6 CO1
effectors and its types, service robot and its application, Artificial
Intelligence in Robotics.

II Actuators and sensors :Types of actuators, stepper-DC-servo-and

brushless motors- model of a DC servo motor-types of transmissions-
purpose of sensor-internal and external sensor-common sensors-
encoders tachometers-strain gauge based force torque sensor-
proximity and distance measuring sensors 6 CO2
Kinematics of robots: Representation of joints and frames, frames
transformation, homogeneous matrix, D-H matrix, Forward and
inverse kinematics: two link planar (RR) and spherical robot (RRP).
Mobile robot Kinematics: Differential wheel mobile robot

III Localization: Self-localizations and mapping - Challenges in

localizations – IR based localizations – vision based localizations – 6 CO3
Ultrasonic based localizations - GPS localization systems.

IV Path Planning: Introduction, path planning-overview-road map path 6 CO4

planning-cell decomposition path planning potential field path
 planning-obstacle avoidance-case studies

Vision system: Robotic vision systems-image representation-object

recognition-and categorization-depth measurement- image data
compression-visual inspection-software considerations

V Application: Ariel robots-collision avoidance robots for agriculture-

mining-exploration-underwater-civilian- and military applications-
nuclear applications-space Applications-Industrial robots-artificial
6 CO5
intelligence in robots-application of robots in material handling-
continuous arc welding-spot welding-spray painting-assembly
operation-cleaning-etc.

Total
Course Outcomes Programme
Outcomes
CO On completion of this course, students will
1 Describe the different physical forms of robot architectures. PO1
2 Kinematically model simple manipulator and mobile robots. PO1, PO2
3 Mathematically describe a kinematic robot system PO4, PO6
4 Analyze manipulation and navigation problems using knowledge of
PO4, PO5, PO6
coordinate frames, kinematics, optimization, control, and uncertainty.
5 Program robotics algorithms related to kinematics, control, optimization,
PO3, PO8
and uncertainty.
Text Book
1 RicharedD.Klafter. Thomas Achmielewski and MickaelNegin, Robotic Engineering and
Integrated Approach, Prentice Hall India-Newdelhi-2001
2 SaeedB.Nikku, Introduction to robotics, analysis, control and applications, Wiley-India, 2 nd
edition 2011
Reference Books
1. Industrial robotic technology-programming and application by M.P.Groover et.al,
McGrawhill2008
2. Robotics technology and flexible automation by S.R.Deb, THH-2009
Web Resources
1. https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_robotics.htm
2. https://www.geeksforgeeks.org/robotics-introduction/

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6
CO 1 S
CO 2 M S
CO 3 S S
 CO 4 S S M
CO 5 S
S-Strong M-Medium L-Low
Marks

Inst. Hours
Category

Credits

External
Subject Code Subject Name L T P S

Total
CIA
Simulation and Modeling Specific Y - - - 4 4 25
75 100
Elective
Course Objectives
Generates computer simulation technologies and techniques, lays the groundwork
for students to comprehend computer simulation requirements, and implements
CO1 and tests a variety of simulation and data analysis libraries and programmes. This
course focuses on what is required to create simulation software environments
rather than just simulations using pre-existing packages
Discuss the concepts of modelling layers of critical infrastructure networks in
CO2
society.
CO3 Create tools for viewing and controlling simulations and their results.
CO4 Understand the concept of Entity modelling, Path planning
CO5 To learn about the Algorithms and Modelling.
Course
UNIT Details No. of Hours
Objectives
Introduction To Modeling & Simulation – What is
Modeling and Simulation? – Complexity Types –
Model Types – Simulation Types – M&S Terms and
Definitions Input Data Analysis – Simulation Input
I 6 CO1
Modeling – Input Data Collection - Data Collection
Problems - – Input Modeling Strategy - Histograms
-Probability Distributions - Selecting a Probability
Distribution.

Random Variate Generation – Random Numbers –

Random Number Generators – General principles –
Inverse Transform Method –Acceptance Rejection
Method –Composition Method –Relocate and
II Rescale Method - Specific distributions-Output Data 6 CO2
Analysis – Introduction -Types of Simulation With
Respect to Output Analysis - Stochastic Process and
Sample Path - Sampling and Systematic Errors -
Mean, Standard Deviation and Confidence Interval -
 Analysis of Finite-Horizon Simulations - Single Run
- Independent Replications - Sequential Estimation –
Analysis of Steady-State Simulations - Removal
oInitialization Bias (Warm-up Interval) -
Replication-Deletion Approach - Batch-Means
Method .

Comparing Systems via Simulation – Introduction –

Comparison Problems - Comparing Two Systems -
Screening Problems - Selecting the Best -
Comparison with a Standard - Comparison with a
III Fixed Performance Discrete Event Simulations – 6 CO3
Introduction - Next-Event Time Advance -
Arithmetic and Logical Relationships - Discrete-
Event Modeling Approaches – Event-Scheduling
Approach – Process Interaction Approach.

Entity Modeling – Entity Body Modeling – Entity

Body Visualization – Entity Body Animation –
Entity Interaction Modeling – Building Modeling
Distributed Simulation – High Level Architecture
(HLA) – Federation Development and Execution
Process (FEDEP) – SISO RPR FOM Behavior
IV 6 CO4
Modeling – General AI Algorithms - Decision Trees
- Neural Networks - Finite State Machines - Logic
Programming - Production Systems – Path Planning
- Off-Line Path Planning - Incremental Path
Planning - Real-Time Path Planning – Script
Programming -Script Parsing - Script Execution.

Optimization Algorithms – Genetic Algorithms –

Simulated Annealing Examples: Sensor Systems
V 6 CO5
Modeling – Human Eye Modeling – Optical Sensor
Modeling – Radar Modeling.

Total 30
Course Outcomes
Course
On completion of this course, students will; Programme Outcomes
Outcomes

CO1 Introduction To Modeling & Simulation, Input Data PO1

Analysis and Modeling.
CO2 Random Variate and Number Generation. Analysis PO1, PO2
of Simulations and methods.
 CO3 Comparing Systems via Simulation PO4, PO6

CO4 Entity Body Modeling, Visualization, Animation. PO4, PO5, PO6

CO5 Algorithms and Sensor Modeling. PO3, PO8

Text Books
Jerry Banks, ―Handbook of Simulation: Principles, Methodology, Advances,
1.
Applications, and Practice‖, John Wiley & Sons, Inc., 1998.
George S. Fishman, ―Discrete-Event Simulation: Modeling, Programming and
2.
Analysis‖, Springer-Verlag New York, Inc., 2001.
References Books
Andrew F. Seila, Vlatko Ceric, Pandu Tadikamalla, ―Applied Simulation
1.
Modeling‖, Thomson Learning Inc., 2003.
Web Resources
1. https://www.tutorialspoint.com/modelling_and_simulation/index.htm
2. https://www.javatpoint.com/verilog-simulation-basics

Mapping with Programme Outcomes:

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8
CO 1 S
CO 2 M S
CO 3 S S
CO 4 S S M
CO 5 S S
S-Strong(3) M-Medium (2) L-Low (1)
Inst. Hours Marks
Category

Credits

External
Subject Code Subject Name L T P O

Total
CIA

Specific
Organizational Behaviour Y - - - 2 2 25 75 100
Elective
Learning Objectives
LO1 To have extensive knowledge onOB and the scope of OB.
LO2 To create awareness of Individual Benaviour.
LO3 To enhance the understanding of Group Behaviour
LO4 To know the basics of Organisaitonal Culture and Organisational Structure
LO5 To understand Organisational Change, Conflict and Power
UNIT Details No. of Hours
INTRODUCTION : Concept of Organizational Behavior (OB):
I 6
Nature, Scope and Role of OB: Disciplines that contribute to OB;
 Opportunities for OB (Globalization, Indian workforce diversity,
customer service, innovation and change, networked
organizations, work-life balance, people skills, positive work
environment, ethics)
INDIVIDUAL BEHAVIOUR:
1. Learning, attitude and Job satisfaction: Concept of learning,
conditioning, shaping and reinforcement. Concept of attitude,
components, behavior and attitude. Job satisfaction: causation;
impact of satisfied employees on workplace.
2. Motivation : Concept; Theories (Hierarchy of needs, X and Y,
Two factor, McClelland, Goal setting, Self-efficacy, Equity
II 6
theory); Job characteristics model; Redesigning jobs,
3. Personality and Values : Concept of personality; Myers-Briggs
Type Indicator (MBTI); Big Five model. Relevance of values;
Linking personality and values to the workplace (person-job fit,
person-organization fit)
4. Perception, Decision Making : Perception and Judgements;
Factors; Linking perception to individual decision making:
GROUP BEHAVIOUR : 1. Groups and Work Teams : Concept :
Five Stage model of group development; Group norms,
cohesiveness ; Group think and shift ; Teams; types of teams;
III Creating team players from individuals and team based 6
work(TBW) 2. Leadership : Concept; Trait theories; Behavioral
theories (Ohio and Michigan studies); Contingency theories
(Fiedler, Hersey and Blanchard, Path-Goal);
ORGANISATIONAL CULTURE AND STRUCTURE :
Concept of culture; Impact (functions and liability); Creating and
IV 6
sustaining culture: Concept of structure, Prevalent organizational
designs: New design options
ORGANISATIONAL CHANGE, CONFLICT AND POWER:
Forces of change; Planned change; Resistance; Approaches
V (Lewin's model, Organisational development);. Concept of 6
conflict, Conflict process; Types, Functional/ Dysfunctional.
Introduction to power and politics.
30
Course
On Completion of the course the students will
Outcomes
CO1 To define OrganisationalBehaviour, Understand the opportunity through OB.
To apply self-awareness, motivation, leadership and learning theories at
CO2
workplace.
CO3 To analyze the complexities and solutions of group behaviour.
CO4 To impact and bring positive change in the culture of the organisaiton.
CO5 To create a congenial climate in the organization.
Reading List
NeharikaVohra Stephen P. Robbins, Timothy A. Judge , Organizational
1.
Behaviour, Pearson Education, 18th Edition, 2022.
2. Fred Luthans, Organizational Behaviour, Tata McGraw Hill, 2017.
Ray French, Charlotte Rayner, Gary Rees & Sally Rumbles, Organizational
3.
Behaviour, John Wiley & Sons, 2011
Louis Bevoc, Allison Shearsett, Rachael Collinson, Organizational Behaviour
4.
Reference, Nutri Niche System LLC (28 April 2017)
Dr. Christopher P. Neck, Jeffery D. Houghton and Emma L. Murray,
5. Organizational Behaviour: A Skill-Building Approach, SAGE Publications, Inc;
2nd edition (29 November 2018).
References Books
Uma Sekaran, Organizational Behaviour Text & cases, 2nd edition, Tata McGraw
1.
Hill Publishing CO. Ltd
GangadharRao, Narayana, V.S.P Rao, Organizational Behaviour 1987, Reprint
2.
2000, Konark Publishers Pvt. Ltd, 1st edition
3. S.S. Khanka, Organizational Behaviour, S. Chand & Co, New Delhi.
4. J. Jayasankar, Organizational Behaviour, Margham Publications, Chennai, 2017.

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8
CO 1 S
CO 2 M S
CO 3 S S
CO 4 S S M
CO 5 S S