Course Description-CSE

1st Semester
Course Name: Engineering Mathematics Course Code: MA101

L-T-P scheme: 3-1-0 Credits: 4

Prerequisite: Students should have basic knowledge of Algebra and calculus.

Objective: This course is aimed:

● To introduce the calculus of functions of two variables and applicability of derivatives and
integrals of vector functions to Analytical geometry and physical problems.
● To make students aware of the basic mathematical concepts and methods which will help them
in learning courses in engineering and Technology.

Learning Outcomes:

Course Description
Outcome
CO1 Understand the rank, eigen values, eigen vectors, diagonalization of matrix;
compute inverse of matrix by Caley-Hamilton theorem.
CO2 Recognize consistent and inconsistent systems of linear equations by the row
echelon form of the augmented matrix, and solve it by Gauss elimination method.
CO3 Interpret derivatives and integrals of multivariable functions geometrically and
physically; implement multivariable calculus tools in engineering, science,
optimization, and understand the architecture of surfaces in plane and space etc.
CO4 Know about piecewise continuous functions, Laplace transforms and its properties;
use of Laplace transform and inverse transform for solving initial value problems.
CO5 Realize importance of line, surface and volume integrals, Gauss and Stokes
theorems and apply the concepts of vector calculus in real life problems.
CO6 Formulate mathematical models in the form of ordinary differential equations and
learn various techniques of getting solutions of linear differential equations of
second order.

Course Contents:

Unit 1: Algebra of matrices, Determinants, Rank, Gauss elimination method, Eigen values and
vectors. Quadratic forms.

Unit 2: Partial differentiation. Taylor’s series. Maxima and minima. Jacobians, Double integrals,
Unit 3: Differential Equations with constants coefficients.

Unit 4: Gradient, divergence and curl. Line and surface integrals, Normal and tangent to a
surface. Gauss and Stokes theorems, Equations to a line, plane, curve and surfaces.

Unit 5: Laplace transforms.

Methodology:
The course will be covered through lectures supported by tutorials. There shall be 3 Lectures per
week where the teacher will explain the theory, give some examples supporting the theory and its
applications. About 12 Tutorial Sheets covering whole of the syllabus shall be given. Difficulties
and doubts shall be cleared in tutorials. Apart from the discussions on the topics covered in the
lectures, assignments/ quizzes in the form of questions will also be given.

Evaluation Scheme:

Exams Marks Coverage

Test-1 15 Marks Syllabus covered upto Test-1
Test-2 25 Marks Syllabus covered upto Test-2
Test-3 35 Marks Full Syllabus
Assignment 10 Marks
Tutorials 5 Marks
Quiz 5 Marks
Attendance 5 Marks
Total 100 Marks

Learning Resources:

Tutorials, lecture slides and books on mathematics-1 will be available on the JUET
server.
Books
1. Erwin Kreyszig: Advanced Engineering Mathematics, Wiley Publishers.
2. Lipshuts, S., Lipsom M.: Linear Algebra, 3rd Ed, Schaum series 2001.
3. B. V. Raman: Higher Engineering Mathematics, McGraw-Hill Publishers.
4. R.K. Jain, S.R.K. Iyenger: Advanced Engineering Mathematics, Narosa Publishing
House, New Delhi.
5. Thomas, G.B., Finney, R.L.: Calculus and Analytical Geometry, 9th Ed., Addison
Wesley,1996.
6. Grewal, B.S. : Higher Engineering Mathematics, Khanna Publishers Delhi.
 Title of Course: Engineering Physics-I Course Code: PH101

L-T Scheme: 3-1-0 Course Credits: 4

Objective: Broadly, the study of Physics improves one’s ability to think logically about the
problems of science and technology and obtain their solutions. The present course is aimed to
offer a broad aspect of those areas of Physics which are specifically required as an essential
background to all engineering students for their studies in higher semesters. The course intends
to impart sufficient scientific understanding of different phenomena associated with Special
relativity, Modern Physics, Statistical physics, atomic physics, and lasers.

Course Outcomes:
Course Description
Outcome
CO1 Describe the limitations of Newton’s laws and explain when special relativity become
relevant,
Learn to Apply the principles of Special Relativity to an extended range of problems
involving
particle kinematics
CO2 Demonstrate the ability to explain the concepts related to the consequences of Special
Relativity, the nature of space-time and related dynamic observables
CO3 Acquired a profound understanding of inadequacy of classical mechanics regarding
phenomena related to microscopic level, Become well versed with the experimental
developments, historical account and importance of probabilistic interpretation
CO4 Understand the basic quantum mechanical ideas and relevant mathematical framework,
approach the solution of one dimensional time independent Schrodinger equation
CO5 Appreciate the importance of applying statistical ideas to explore thermodynamic
variables, Developed ability to identify and apply appropriate statistical method for
describing the assembly of microscopic particles, comprehend basic properties and
working of Laser systems

Course Contents:
Unit-I (Theory of Special Relativity): Frames of reference, Galilean transformation, Michelson
Morley Experiment, Postulates of special theory of relativity, time dilation and length
contraction, twin paradox, Lorentz transformations, addition of velocities, Relativistic Doppler
effect, Mass variation with velocity, Mass-energy relation.

Unit-II (Introduction to Modern Physics):

Quantization of Radiation, Black body radiation, Rayleigh-Jeans law, Planck’s law of radiation
Wien's law, Stefan’s law, Photoelectric effect Compton scattering, Atomic spectra, Bohr model
of hydrogen atom, Frank hertz experiment, Matter waves, de Broglie hypothesis, Davisson
Germer experiment

Unit III Quantum Mechanics

Wave packets, phase and group velocity, Heisenberg’s uncertainty principle, Schrödinger wave
equation and its applications to the free particle in a box, potential barrier and Harmonic
oscillator
Unit-IV (Statistical Mechanics): Maxwell-Boltzmann, Bose-Einstein and Fermi-Dirac
distributions and their applications.

Unit- V Laser Physics & Applications

Fundamental ideas of stimulated and spontaneous emission, Einstein’s coefficients, Principle
and working of laser, Different types of lasers (He-Ne Laser, Ruby Laser, Semiconductor Laser),
Applications of Lasers

Text Books and References:

1. A. Beiser, Perspectives of Modern Physics, Tata McGraw Hill.
2. J R Taylor, C D Zafiratos, M A Dubson, Modern Physics for Scientist &
1. Engineers, Pearson Education.
2. K Krane, Modern Physics, Wiley India
3. J Bernstein, P M Fishbane, S. Gasiorowicz, Modern Physics, Pearson
4. Education.
5. B. B. Laud, Laser and Non-Linear Optics, New Age International (P) Ltd.
6. R. Resnick, Relativity, New Age.
Title: English Code: HS101

L-T-P scheme: 2-0-2 Credit: 3

Prerequisite: None

Objective:
1. To enable understanding of basics of communication in Business environment.
2. To provide insight into structural aspect of communication in business.
3. To impart knowledge about communication theory and develop skills in oral and non
verbal communication.
4. To improve skills as critical readers, thinkers, listener and writer.

Learning Outcomes:

Course Description
Outcome
Outline the basic concept of verbal/ nonverbal skills to understand the role
CO1
of effective communication in personal & professional success.
Describe drawbacks in listening patterns and apply listening techniques for
CO2
specific needs.
Develop the understanding to analyze, interpret and effectively summarize
CO3
a variety of textual content
Discuss a given technical/non-technical topic in a group setting and arrive
CO4
at generalizations/consensus.
CO5 Create effective presentations
Create professional and technical documents that are clear and adhering to
CO6
all the necessary convention.

Course Content:
Unit-1: Concept and Nature of Communication : Definition of Communication,
Process & Stages of Communication, Barriers to Communication, Channels of
Communication.
Unit-2: Listening Skills: The listening process, Importance of listening, Purpose and
types of listening, Hearing and listening, Listening with a purpose, Barriers to listening.
Unit-3: Speaking/Oral Skills: Importance of acquiring oral skills, Visual aids, Body
Language, Delivery, Pronunciation, Use of connectives Organization of matter:
Metadiscourse features, Textual organization, 7 C’S of effective communication ,
Improving vocabulary by learning Root words in English, Some foreign words, Reading
comprehension, Some important synonyms and antonyms, commonly confused words,
Etiquettes & grooming.
Unit-4: Reading Skills: Skimming and Scanning, Intensive and extensive reading, SQ3R
Technique
Unit-5: Writing Skills: Business letters, Memo, Circulars, Notices, Report writing,
resume writing, Agenda & Minutes writing, Tips on clear writing Translation- Hindi to
English, Translation -English to Hindi.
 Unit-6: Introduction to Modern Communication Media: Technology based
communication tools, Committee types, Advantages, Conferences, Audio-video
conferencing, Barriers and overcoming negative impact.
Unit-7: Public Speaking and Interviewing Strategies: Speech Preparation, Theory of
group discussion, Participation in Group discussion, Oral presentation, Power point
presentation ,Tips for successful job interview, Do's and don'ts while appearing for
interview, Mock interview, Some interview questions, Telephonic interview tips, Resume
writing

Evaluation Scheme:
Exams Marks Coverage
Test-1 15 Marks Based on Unit-1 & Unit-2
Based on Unit-3,& Unit-4 and around 30%
Test-2 25 Marks
from coverage of Test-1
Based on Unit-5 to Unit-7 and around 30% from
Test-3 35 Marks
coverage of Test-2
Assignment 10 Marks
Tutorials 5 Marks
Quiz 5 Marks
Attendance 5 Marks
Total 100 Marks

Teaching Methodology:

The course will be taught with the aid of lectures, handouts, case studies, Task-based language
learning, and comprehensive language learning through language lab.

Learning Resources:
Lecture slides and e-books on ENGLISH (will be added from time to time): Digital copy will be
available on the JUET server.

Text Book:
1. K.K. Sinha- Business Communication (Galgotia Publications)

Reference Books:
1. R.C. Bhatia- Business Communication (Ane Books Pvt. Ltd.)
2. P.D. Chaturvedi – Business Communication (Pearson Education, 1st Edition 2006).
3. Lesikar RV & Pettit Jr. JD – Basic Business Communication: Theory & Application
(Tata Mc Graw Hill, 10thEdition)
4. Wren & Martin, High School English Grammar & Composition – S. Chand & Co.
Delhi.
5. Raman Meenakshi & Sharma Sangeeta, Technical Communication-Principles &
Practice –O.U.P. New Delhi. 2007.
6. Mitra Barum K., Effective Technical Communication – O.U.P. New Delhi. 2006.
7. Better Your English- a Workbook for 1st year Students- Macmillan India, New Delhi.
8. Raymond Murphy,’ Essential English Grammar’, Cambridge University Press.
Title: Computer Programming Code: CS101
L-T-P scheme: 3-1-0 Credit: 4

Prerequisite: There is no prerequisite in this course; however, students having any prior
experience of programming are desirable.

Objective:

1. To provide exposure to problem-solving through programming.

2. To provide students with understanding of code organization and functional hierarchical
decomposition with using complex data types.

Learning Outcomes:

Course Description
Outcome
Makes students gain a broad perspective about the uses of computers in
CO1
engineering industry.
CO2 Develops basic understanding of computers, the concept of algorithm and
algorithmic thinking.
Develops the ability to analyze a problem, develop an algorithm to solve
CO3
it.
Develops the use of the C programming language to implement various
CO4
algorithms, and develops the basic concepts and terminology of
programming in general.
CO5 Introduces the more advanced features of the C language

Course Content:

Unit-1: Introduction to Programming: Basic computer organization, operating system, editor,

compiler, interpreter, loader, linker, program development. Variable naming, basic function
naming, indentation, usage and significance of comments for readability and program
maintainability. Types of errors, debugging, tracing/stepwise execution of program, watching
variables values in memory. Constants, Variables and data Types Character Set, C tokens,
Keywords and Identifiers, Constants, Variables, Data types, Declaration of Variables, assigning
values to variables, typedef, and Defining symbolic constants. printf & scanf function.

Unit-2: Operators and Expression: Introduction, Arithmetic Operators, Relational Operators,

Logical Operators, Assignment Operators, Increment and Decrement Operators, Conditional
Operators, Special Operators, Evaluation of expressions, Precedence of arithmetic operators,
Type conversions in expressions, Operator precedence and associativity.

Management Input and Output Operators: Introduction, reading a character, writing a

character, formatted input, formatted output.

Unit-3: Decision Making Branching: Introduction, Decision making with IF statement, the IF-
ELSE statement, nesting of IF-ELSE statement, ELSE-IF ladder, SWITCH statement, ternary
operator, and the GOTO statement.
Looping: Introduction, the WHILE statement, the DO statement, The FOR statement, Break and
Continue.

Unit-4: Array: Introduction, One-dimensional arrays, Two-dimensional arrays, arrays, Concept

of Multidimensional arrays.

Handling of Character strings: Introduction, Declaring and initializing string variables, reading
string from terminal, writing string to screen, String, Operations: String Copy, String Compare,
String Concatenation and String Length (using predefined functions & without using them),
Table of strings.

Unit-5: User-Defined Functions (UDF): Introduction, need for user-defined functions, the form
of C function, elements of UDF, return values and their types, Calling a function, category of
functions, Nesting of functions, Recursion, Functions with arrays, The scope and Lifetime of
variables in functions, multi file program.

Structures and Unions: Introduction, Structure definition, declaring and initializing Structure
variables, accessing Structure members, Copying & Comparison of structures, Arrays of
structures, Arrays within structures, Structures within Structures, Structures and functions,
Unions.

Unit-6: Pointers: Introduction, understanding pointers, Accessing the address of variable,

Declaring and initializing pointers, accessing a variable through its pointer, Pointer expressions,
Pointer increments and scale factor, Pointers and arrays, Pointers & character strings, Pointers &
Functions, Function returning multiple values, Pointers and structures.

File Management in C and CONSOLE I/O: Introduction, Defining files and its Operations,
Error handling during I/O operations, Random access files, Command line arguments. Types of
files, File vs. Console, File structure, File attributes, Standard i/o, Formatted i/o, Sample
programs.

Teaching Methodology:
This course is introduced to help students understand the discipline of programming. The
programming language used to teach this course is C. Starting from the basic computer
architecture, the student will slowly be exposed to program designing and later to programming
fundamentals. The entire course is broken down into six separate units, from fundamentals of
programming to some complex programming structures like pointers. This theory course is well
complemented by a laboratory course under the name Software Development Fundamentals Lab
in the same semester that helps a student learn with hand-on experience.

Evaluation Scheme:

Exams Marks Coverage

Test-1 15 Marks Based on Unit-1 & Unit-2
Based on Unit-3 & Unit-4 and around 20-30%
Test-2 25 Marks
from coverage till Test-1
Based on Unit-5 to Unit-6 and around 30% from
Test-3 35 Marks
coverage till Test-2
Assignment 10 Marks
Tutorials 5 Marks
Quiz 5 Marks
Attendance 5 Marks
Total 100 Marks

Learning Resources:

Tutorials and lecture slides on Software Development Fundamentals (will be added from
time to time): Digital copy will be available on the JUET server.

Text Book:

[1] Programming in ANSI C by E. Balguruswamy, Tata Mc-Graw Hill.

[2] Programming With C, Schaum Series.

Reference Books/Material:
[1] The ‘C’ programming language by Kernighan and Ritchie, Prentice Hall
[2] Computer Programming in ‘C’ by V. Rajaraman, Prentice Hall
[3] Programming and Problem Solving by M. Sprankle, Pearson Education
[4] How to solve it by Computer by R.G. Dromey, Pearson Education

Web References:
[1] http://www2.its.strath.ac.uk/courses/c/
Notes on C programming by University of Strathclyde Computer Centre. This tutorial
was awarded the NetGuide Gold Award during the 1990s.

[2] http://www.princeton.edu/~achaney/tmve/wiki100k/docs/C_%28programming_langu
age%29.html
This site contains notes on C programming from Princeton University, USA.
These are very useful for students who are learning C as their first programming
Language.

[3] http://www.stat.cmu.edu/~hseltman/Computer.html
Online reference material on Computers and Programming from Carnegie Mellon
University, Pittsburgh, USA

[4] http://projecteuler.net/
Collection of mathematical problems which make you use your programming skills
Title: Engineering Physics Lab-I Code: PH201
L-T-P scheme: 0-0-2 Credit: 1
Learning Outcomes

Course Description
Outcome
CO1 Demonstrate ability to collect experimental data and understanding the working
procedures within the precautionary limits

CO2 Acquired the ability to analyze the experimental data and related errors in a reflective,
iterative and responsive way
CO3 Developed understanding of the basic concepts related to Modern Physics, Basic Solid
State Physics and Optics
CO4 Acquired a first hand and independent experience of verifying Kirchoff’s circuit laws
and related concepts e.g. resistivity, measurement of resistance
CO5 Appreciate the importance of the laboratory work culture and ethics that is intended to
impart features like regularity, continuity of self evaluation and honesty of reporting the
data

List of Experiments

1. To study the variation of magnetic field along the axis of Helmholtz Galvanometer and to
determine its reduction factor.

2. To determine the resistance per unit length of a Carey Foster’s bridge and to obtain the
specific resistance of a given wire.

3. To determine the wavelengths of spectral lines Red, Green and Violet of mercury using
plane transmission grating.

4. To determine the specific rotation of cane sugar solution using Bi-quartz polarimeter.

5. To observe Newton’s rings and to determine the wavelength of sodium light.

6. To study the CRO and function generator by producing the following waveforms.

i. 10kHz, 8Vp-p(sine wave, square wave, triangular wave)

ii. 4kHz, 6Vp-p(sine wave, square wave, triangular wave)

iii. 10kHz, 8Vpeak(sine wave, square wave, triangular wave)

iv. 4kHz, 6Vpeak(sine wave, square wave, triangular wave)

7. To verify the Kirchhoff’s current law.

8. To verify the Kirchhoff’s voltage law.

 Title: Computer Programming Lab Code: CS201

L-T-P scheme: 0-0-4 Credit: 2

Prerequisite: Experience in programming is desirable.

Objective:

1. To provide exposure to problem-solving through programming.

2. To provide students with understanding of code organization and functional hierarchical
decomposition with using complex data types.
3. To give the student hands-on experience with the concepts.

Learning Outcomes:
Course Description
Outcome
CO1 Makes students gain a broad perspective about the uses of computers in
engineering industry.
CO2 Develops basic understanding of computers, the concept of algorithm and
algorithmic thinking.
CO3 Develops the ability to analyze a problem, develop an algorithm to solve
it.
CO4 Develops the use of the C programming language to implement various
algorithms, and develops the basic concepts and terminology of
programming in general.
CO5 Introduces the more advanced features of the C language

Course Content:

The following assignments will be carried out in synchronization with the theory classes.

Unit-1: Introduction to programming Environment (Linux commands, editing tools such as vi

editor, sample program entry, compilation and execution). Development of programs using
multiple arithmetic and logical operators. Programs for Roots of quadratic equation, conversion
of units etc.

Unit-II: Programs using simple control statements such as if else, while, do while etc. Making a
program for a calculator for example. Extracting the digits of an integer, reversing digits, finding
sum of digits etc.

Unit-III: Programs using For loop, switch statement etc. For example, Finding average of
numbers, printing multiplication tables etc. Checking for primes, generation of Armstrong
numbers. Generation of the Fibonacci sequence, Finding the square root of a number, calculation
of factorials, printing various patterns using for loop. The greatest common divisor of two
integers, Raising a number to large power.
Unit-IV: Programs using Arrays: declaring and initializing arrays. Program to do simple
operations with arrays. Strings – inputting and outputting strings. Using string functions such as
strcat, strlen etc. Writing simple programs for strings without using string functions.Finding the
maximum number in a set, Array order reversal, Finding maximum number from an array of
numbers Removal of duplicates from an ordered array,

Unit-V: Selection/ Bubble/ Insertion sort, create a linked list, traverse a linked list, insert a node
and delete a node form the list. Recursion and related examples such as Tower of Hanoi,
computing factorial etc. Practice sessions and sessions for missed labs

Units to Lab Mapping:

Unit Labs
I 1, 2, 3
II 4, 5
III 6, 7, 8
IV 9, 10, 11
V 12, 13, 14

Teaching Methodology:

This course is introduced to help students understand the discipline of programming. The
programming language used to teach this course is C. Starting from the programming
environment setup, the student will slowly be exposed to program designing and later to
programming fundamentals. The entire course is broken down into six separate units, from
fundamentals of programming to some complex programming structures like pointers. This
theory course is well complemented by a laboratory course under the name Software
Development Fundamentals Lab in the same semester that helps a student learn with hand-on
experience.

Evaluation Scheme:

Exams Marks Coverage

P-1 15 Marks Based on Lab Exercises: 1-6
P-2 15 Marks Based on Lab Exercises: 7-13
Viva 20 Marks
Demonstration 20 Marks
Day-to-Day Work 70 Marks
Lab Record 15 Marks
Attendance & Discipline 15 Marks
Total 100 Marks

Learning Resources:

Study material of Software Development Fundamentals Lab (will be added time to time):
Digital copy will be available on the JUET server.
Text Book:

1. Programming in ANSI C by E. Balguruswamy, Tata Mc-Graw Hill.

2. Programming With C, Schaum Series.

Reference Books/Material:

1. The ‘C’ programming language by Kernighan and Ritchie, Prentice Hall

2. Computer Programming in ‘C’ by V. Rajaraman, Prentice Hall
3. Programming and Problem Solving by M. Sprankle, Pearson Education
4. How to solve it by Computer by R.G. Dromey, Pearson Education

Web References:

1. http://www2.its.strath.ac.uk/courses/c/
a. Notes on C programming by University of Strathclyde Computer Centre. This
tutorial was awarded the NetGuide Gold Award during the 1990s.

2. http://www.princeton.edu/~achaney/tmve/wiki100k/docs/C_%28programming_language
%29.html
a. This site contains notes on C programming from Princeton University, USA.
These are very useful for students who are learning C as their first programming
Language.

3. http://www.stat.cmu.edu/~hseltman/Computer.html
a. Online reference material on Computers and Programming from Carnegie Mellon
University, Pittsburgh, USA

4. http://projecteuler.net/
a. Collection of mathematical problems which make you use your programming
skills
 Title: Workshop Practices Code: ME201
L-T-P scheme: 0-0-3 Credit: 1.5

Prerequisite: Students must have the knowledge of fundamental principles of Physic and
Chemistry upto class 12th which helps them to understand the various process of
Workshop Lab.
Objective:
1. To demonstrate students, the basic manufacturing processes of Workshop lab: Carpentry,
Fitting, Welding, Machining and Casting Processes.
2. To develop effective skills in students to identify the manufacturing process with its
applications
3. To be able to perform basic manufacturing processes safely.

Learning Outcomes:

Course Description
Outcome

CO1 Identify the various processes of manufacturing.

CO2 Capable to explain the use of various holding, measuring, marking and cutting tools of
workshop

CO3 Prepare a useful job by performing the various processes in proper sequence safely

CO4 Apply Bernoulli’s theorem to analyze the liquid metal velocity in casting process.

CO5 Develop the skills to join two metallic specimen using welding process

CO6 Work as a team on a project

Course Content:

Carpentry Shop
1. To study about various tools/equipments used in carpentry shop
2. To make Cross lap /T joint as per given specification
3. To make Cross lap /T joint as per given specification
Foundry Shop
1. To study about various tools used in foundry shop.
2. To prepare a green sand mould with the help of a given pattern.
3. To perform permeability test on moulding sand
Machine Shop
1. To study various machine tools such as lathe, milling, shaper, drilling, grinding, EDM
drill and cutting tools used by them.
2. To perform turning, step turning and taper turning operations on lathe machine
3. To perform threading operation on the lathe machine
Fitting Shop
1. To study about various tools used in fitting shop.
 2. To make a fitting job as per given drawing.
Welding Shop
1. To study various types of welding processes available in the workshop such as Electric
arc welding, TIG and MIG welding, gas welding and spot resistance welding,
2. To prepare welding joint by using Electric arc welding/gas welding
3. To prepare welding joint by using Spot Resistance welding

Teaching Methodology:
This Lab course has been introduced to help a student to learn with hand-on experience on
machines. The entire course is broken down into fourteen experiments. Experiments are
performed different shop wise by taking the proper safety precautions. Workshop lab includes
five shops namely: Carpentry, Foundry, Machining, Fitting and Welding. Basic principles of
manufacturing processes are applied to prepare a job. Students learn here how to handle the real
world problems by using technical skills. The way of experimentation here realizes the students
that they are now moving on an Engineering path. This Lab course will enable a student to learn
with hand-on experience.
Evaluation Scheme:

Exams Marks Coverage

P-1 15 Marks Based on Lab Experiments: 1-7
P-2 15 Marks Based on Lab Experiments: 8-14
Viva 20 Marks
Demonstration 20 Marks
Day-to-Day Work 70 Marks
Lab Record 15 Marks
Attendance & Discipline 15 Marks
Total 100 Marks

Learning Resources:
Laboratory Manual available in Lab. Study material of Workshop Lab (will be added time to
time): Digital copy will be available on the JUET server.

Text Books:
[1] “Workshop Technology Volume- I & II”, B.S. Raghuvanshi, Dhanpat Rai & Co.
[2] “Workshop Technology Volume-I & II”, Khanna Publisher.
Reference Books:
[1] “Workshop Technology Vol.- 1, 2, 3 & 4”, Butterworth-Heinemann.
[2] “Material Science & Engineering”, W. D. Callister, John Wiley

Web References:
[1] https://nptel.ac.in/courses/112/107/112107219/

[2] https://nptel.ac.in/courses/112/107/112107144/
 Course Description
IInd Semester
Title: Life Skills and Effective Communication Code: HS104
L-T-P scheme: 1-0-2 Credit: 2

Prerequisites: None

Objective:

1. To employ positive behavior management techniques and to develop skills to manage their own
behavior effectively
2. To develop one's personality by being aware of the self, connecting with others, reflecting on the
abstract and the concrete.
3. To enhance the employability and maximize the potential of the students by introducing them to
the principles that underlying personal and professional success, and help them acquire the skills
needed to apply these principles in their lives and careers.

Learning Outcomes:
CO1 Outline different life skills required in personal and professional life.
CO2 Describe the application of different theoretical perspectives within the field of motivation and
applying these motivation theories to everyday settings (e.g., business, social interactions,
education)
CO3 Develop the understanding of personality and shaping behavior through personality
CO4 Identify the basic mechanics of perception by demonstrating these through presentations.
CO5 Apply well-defined techniques to cope with emotions and stress and develop an awareness of the
self.
CO6 Understand the basics of leadership and Learning

Course Content:
Unit-1: Overview of Life Skills: Meaning and significance of life skills, Life skills identified by WHO:
Self-awareness, Empathy, Critical thinking, Creative thinking, Decision making, problem solving,
Effective communication, interpersonal relationship, coping with stress, coping with emotion.
Unit-2: Motivation: Morale and Morale Building, Need and Importance of motivation, Process and
types of motivation, Theories of motivation, Essentials of Good Motivation system
Unit-3: Overview of Personality concept and types, Personality traits, Factors that help in shaping
personality, Theories of personality, Measurement of personality
Unit-4: Perception: - Factors affecting perception, Perceptual mechanisms Perceptual errors and
distortions, Behavioral applications of perceptions
Unit-5: Self Awareness, Coping with emotions: Identifying and managing emotions, harmful ways of
dealing with emotions, Stress Management: Stress, reasons and effects, identifying stress, Managing
Stress
Unit-6: Conflict Management –sources, process and resolution of conflict
Unit-7: Leadership: Need for Leadership, Models of leadership development, and Characteristics of a
good leader.
Unit-8: Learning: Concepts and Theories, classical conditioning, operant conditioning, Biological
influences, Cognitive influences, Social learning theory, Behavioral modification theory

Teaching Methodology:
Life skills are those competencies that provide the means for an individual to be resourceful and positive
while taking on life's vicissitudes .This course will equip students with the social and interpersonal skills
that enable them to cope with the demands of everyday life. There will be a particular focus on social-
cognitive processes and how situational factors trigger various emotions and corresponding motives that
can then drive behavior. The main objectives of this course is to build self-confidence, encourage
critical thinking, foster independence and help students to communicate more effectively

Evaluation Scheme:
Exams Marks Coverage
Test-1 15 Marks Based on Unit-1, Unit-2 & Unit-3
Based on Unit-4 & Unit-5 and around 30% from
Test-2 25 Marks
coverage of Test-1
Based on Unit-6, Unit-7 & Unit-8 and around
Test-3 35 Marks
30% from coverage of Test-2
Assignment 10 Marks
Tutorials 5 Marks
Quiz 5 Marks
Attendance 5 Marks
Total 100 Marks

Learning Resources:
Case studies, video lectures and lecture slides on Life Skills (will be added from time to time):
Digital copy will be available on the JUET server.

Text Book:
1. “Effective Communication and Soft Skills”; Nitin Bhatnagar, Pearson Education
India,1e, 2011
2. “Personality Development and Soft Skills”; Barun Mitra, Oxford Higher Education,2016
3. “Sizzling Soft Skills for Spectacular Success”; P. Ameer Ali, Notion Press, 2017
4. “Organizational Behavior”; Stephen P. Robbins, Timothy A. Judge, Neharika Vohra,
Pearson Education India, 16e, 2016
5. “Managing Organisations”; Rachna Chaturvedi, Vikas Publications, 2013

Reference Books/Material:
1. “The Power of Your Subconscious Mind”; Joseph Murphy, General press, 2015
2. “The Life-Changing Magic of Tidying Up: The Japanese Art of De cluttering and
Organizing”; Marie Kondō, 1e,Ten speed Press, 2011
3. “The Power of Habit: Why We Do What We Do in Life and Business”; Charles Duhigg,
Random House, 2012
Course Title: Discrete Mathematics Course Code: MA105

L-T-P scheme: 3-1-0 Credits: 4

Objectives:

The aim of the course is to cover the basic principles sets relations functions partially ordered set, lattice,
Boolean algebra and its applications. The main objective of the course is to develop in student, an
intuitive understanding of graphs by emphasizing on the real world problems.

Course Outcomes:
At the end of the course, the student is able to:
CO1 Employ De Moivre’s theorem in a number of applications to solve numerical problems.

CO2 Appreciate the definition and basics of graphs along with types and their examples.

CO3 Visualize the applications of graph theory to network flows. Understand the notion of
planarity and coloring of a graph. Relate the graph theory to the real-world problems.

CO4 Understand the definition of a tree and learn its applications to fundamental circuits.

CO5 Solve real-life problems using finite-state and Turing machines

CO6 Learn about partially ordered sets, lattices and their types, Boolean algebra and Boolean
functions, logic gates, switching circuits and their applications.

Course Contents:

Unit 1: Basics of set theory, Mathematical induction. Relations, Equivalence relation,

partial- ordered relation algorithms and functions.
Unit 2: Big O notation, Proposition, Basic logical operators, Propositional functions and

Quantifiers.
Unit 3: Graphs and related definitions, Eulerian and Hamiltonian graphs, Graph

colorings. Trees, Algebraic expressions and Polish notation, shortest path.

Unit 4: Algebraic Systems. Lattice and Boolean Algebra.

Unit 5: Language, Finite State Automata and Machines. Grammars.

Methodology:
The course will be covered through lectures supported by tutorials. Apart from the discussions on the
topics covered in the lectures assignments/ quizzes in the form of questions will also be given.

Evaluation plan:

Exams Marks Coverage

Test-1 15 Marks Based on Unit-1
Based on Unit-2 & Unit-3 and around 30% from
Test-2 25 Marks
coverage of Test-1
Based on Unit-4 to Unit-5 and around 30% from
Test-3 35 Marks
coverage of Test-2
Assignment 10 Marks
Tutorials 5 Marks
Quiz 5 Marks
Attendance 5 Marks
Total 100 Marks

References:
1. B. A, Davey & H. A. Priestley (2002). “Introduction to Lattices and Order” (2nd edition) Cambridge
University, Press.
2. Edgar, G. Goodaire & Michael M. Parmenter (2018). “Discrete Mathematics with Graph Theory”
(3rd edition). Pearson Education.
3. Rudolf Lidl & Günter Pilz (1998). “Applied Abstract Algebra” (2nd edition).Springer.
4. Kenneth H. Rosen (2012). “Discrete Mathematics and its Applications: With Combinatorics and
Graph Theory” (7th edition), McGraw-Hill.
5. C. L. Liu (1985). “Elements of Discrete Mathematics” (2nd edition). McGraw- Hill.
 Title of Course: Engineering Physics-II Course Code: PH102
L-T Scheme: 3-1-0 Course Credits: 4

Objective:

Broadly, the study of Physics improves one’s ability to think logically about the problems of science and
technology and obtain their solutions. The present course is aimed to offer a broad aspect of those areas
of Physics which are specifically required as an essential background to all engineering students for
their studies in higher semesters. At the end of the course, the students will have sufficient scientific
understanding of basic vector calculus, electrostatics, magnetostatics, electromagnetic fields and waves,
basic understanding of physics of semiconducting materials

Course Outcomes:
Course Description
Outco
me
CO1 Learn to apply the basic concepts of vector calculus and understanding of various co-
ordinate
systems and related properties, Demonstrate basic understanding of formulation and
deduction
of electric field produced by static charge distributions
CO2 Evaluate the electrostatic field due to symmetric charge distributions, Understand the
utility of formulation of electric potential and solve related problems using special
techniques and boundary conditions
CO3 Acquired understanding of electrostatic fields inside matter, Explain the magnetic field due
to moving charge distribution, evaluate the magnetic field due to current distribution in
space,
CO4 appreciate the importance of Maxwell’s equations and understand the electromagnetic
wave propagation in free space Categorisation of materials on the basis of band structure
CO5 Developed understanding of quantum mechanical origin of band formation in solids,
describing the energy state of electrons in crystalline materials, comprehend basic carrier
properties

Course Content:
Unit I (Electrostatics)
Review of vector calculus, Cartesian, spherical polar and cylindrical co-ordinate systems, concept of
gradient, divergence and curl, Coulomb’s law, Gauss law and its applications, Boundary condition on
electrostatic field, electric potential, Laplace equation, Poisson equation and related boundary value
problems, capacitance, electrostatic fields in matter [10]
Unit II (Magnetostatics)
Lorentz force, cyclotron formula, line, surface and volume currents, , Biot-Savart law and its
applications, Ampere’s law and its applications, equation of continuity, Faraday’s law of
electromagnetic induction, boundary conditions on magnetic field, Magnetic field in matter
[08]
Unit III (Electromagnetic field)
Maxwell’s equations in free space and matter, Maxwell correction to Ampere’s law, Electromagnetic
waves in free space and matter, Transverse nature of em waves and Polarization, Propagation of
electromagnetic field in free space and Poynting vector, Poynting theorem , Normal incidence of em
waves [10]
Unit IV (Elements of Solid State Physics)
Basic ideas of bonding in solids, Crystal structure, X-ray diffraction, Band theory of solids, Distinction
between metals, semiconductors and insulators [04]
Unit V (Physics of Semiconductors)
Band theory of solids, Kronig Penney model, effective mass, Direct and indirect bandgap
semiconductors, optical and thermal properties, Fermi-Dirac Distribution in semi-conductors,
Equilibrium carrier concentrations in intrinsic and extrinsic semiconductors, Fermi energy variation
with temperature and impurity concentration, Hall Effect in semiconductors, P-N junction
characteristics [10]

Text/ Reference Books:

1. D.J. Griffiths, Introduction to electrodynamics, Prentice Hall of India Ltd.
2. B.G. Streetman, S. Banerjee, Solid State Electronic Devices
3. Semiconductor Physics and Devices, Donald A. Neamen
4. Boylstad and Nashelsky, Electronic Devices and Circuits, PHI, 6e, 2001.
5. J. Reitz, F. Milford and R. Christy, Foundation of Electromagnetic Theory,
Narosa Publishing.
6. J. Millman and C.C. Halkias, Electronic Devices and Circuits, Millman,
McGra-Hill
Title: Electrical Science Code: EC101
L-T-P Scheme: 3-1-0 Credit: 4

Prerequisite: Students must have studied the core concepts of “Physics-1”.

Course Objectives:
1. This course is designed for developing the understanding about basics of electrical and electronics
concepts.
2. In this course students will have an enough idea about the working of systems and enable them to
analyze a circuit.

Learning Outcomes:
1. The students shall acquire the generic skills to study & analyze the electrical and electronic systems.
2. This course will enable them to think and design various applications of the electrical and
electronics at basic level.
The student will be able to:
Course Description
Outcome
CO1 Understand the basic electrical and electronics component and their importance
determine the current, voltage and power.
CO2 Apply networks laws and theorems to solve electric circuits and may understand
circuit reduction techniques with their advantages.
CO3 Understand charging discharging Steady state and transient
CO4 Demonstrate the use of semiconductor diodes in various applications.
CO5 Discuss and explain the working of transistors Amplifiers, their configurations
and applications.
CO6 Analysis concept and two port networks simplification technique.

Course Content:
Unit I: Basic Electrical Circuit: Electromotive Force (EMF), Terminal Voltage; Resistance (R),
Inductance (L) and Capacitance (C) from (i) Circuit, (ii) Energy, and (iii) Geometrical Points of View;
Voltage Divider, Current Divider; Star-Delta Transformation; Voltage Source and Current Source,
Source Transformation, Combination of Sources; Controlled (Dependent) Sources. Unit 2:
Methods of Analysis: Kichhoff’s Circuit Laws; Loop-Current Analysis, Mesh Analysis; Node-Voltage
Analysis; Choices of Method of Analysis.
Unit 3: Network Theorems (DC Circuits):Superposition Theorem; Thevenin’s Theorem; Norton’s
Theorem; Maximum Power Transfer Theorem.

Unit 4: DC Transients:Simple RL Circuit, Time Constant, Decay and Growth of Current; Simple RC
Circuit, Discharging of a Capacitor, Charging of a Capacitor.

Unit 5: Two-Port Networks: Impedance, Admittance, Hybrid, Transmission Parameters; Equivalent

Networks.

Unit 6: Diodes and its Applications: Unidirectional property, PN-junction with no bias, with forward
bias and with reverse bias, V-I characteristics, Comparison of Si and Ge diodes,Temperature effects,
Diode resistance (static and dynamic), Diode equation, Ideal diode, Circuit model of a diode. Half-wave
and full-wave (centre tap and bridge) rectifiers, PIV rating of diode, Performance of half-wave and full-
wave rectifiers, Shunt capacitor filter. Clippers: Series and Parallel, Limiters, Clampers. Zener diode,
Analysis of Zener voltage regulator. LED, varactor diode .

Unit 7: Transistor: BJT Structure, Working of a transistor, Transistor current equation, Collector
reverse saturation current, DC alpha of a transistor. The three configurations, CB and CE input and
output characteristics.

Teaching Methodology:
Lectures would be interactive and it would cover the core concepts that are explained in the text and
reference materials with adequate examples.

Evaluation Scheme:
Exams Marks Coverage
Test-1 15 Based on Unit-1 & Unit-2
Based on Unit-3, Unit-4 & Unit-5 and around 30%
Test-2 25
from coverage of Test-1
Based on Unit-6 to Unit-7 and around 30% from
Test-3 35
coverage of Test-2
Assignment 10 Based on Unit-1, Unit-2 & Unit-3
Tutorials 5 Based on Unit-4 & Unit-5
Quiz 5 Based on Unit-6 & Unit-7
Attendance 5 Based on attendance in the theory classes
Total 100
Learning Resources:
Tutorials sheets, lecture slides and handwritten notes on Electrical circuit, Electrical Science and
Basic Electronics (will be added from time to time): Digital copy will be available on the JUET server.

Text-Books:

1. D.C. Kulshreshtha, “Basic Electrical Engineering”, McGraw Hill Education, 2009.

2. W.H. Hayt, J. E. Kemerlay & S.M. Durbin, “Engineering Circuit Analysis (Sixth Edition)”,
McGraw Hill, 2006.
3. R.C. Dorf & J.A. Svoboda, “Introduction to Electric Circuits”, John Wiley, 2004.
4. D.S. Chauhan & D.C. Kulshreshtha, ‘Electronics Engineering’, New Age, 2e, 2009.
5. D.C. Kulshreshtha, ‘Electronic Devices and Circuits’, New Age, 2e, 2006.

References:

1. Van Valkenburg, “Network Analysis”, Prentice-Hall India Ltd., 2001.

2. Abhijit Chakrabarti, Sudipta Nath, Chandan Kumar Chanda, “Basic Electrical Engineering”,
Tata McGraw Hill Publishing Co, 2008.
3. Vincent Del Toro, “Principles of Electrical Engineering”, Prentice Hall of India.
4. Kumar and Jain, ‘Electronic Devices and Circuits’, PHI, 2007.
5. Boylstad and Nashelsky, ‘Electronic Devices and Circuits’, PHI, 6e, 2001.

Web References:
1. https://www.electrical4u.com/electrical-engineering-objective-questions-mcq/
2. https://www.pdfdrive.com/basic-electric-circuit-analysis-books.html
3. https://lecturenotes.in/subject/842

Journals References:
1. Circuits, Systems, and Signal Processing (CSSP), Springer
2. Journal of Electrical & Electronic Systems
3. International Journal of Circuit Theory and Applications, Wiley
 Title of Course: Object Oriented Programming Course Code: CS102
L-T-P Scheme: 3-1-0 Course Credit: 4

Prerequisites:
Students must have already registered for the course, “Software Development Fundamentals”

Objectives:
To strengthen their problem solving ability by applying the characteristics of an object-oriented
approach and to introduce object oriented concepts in C++.
Learning Outcomes
Course Outcome Description
CO1 List various principles of Object-Oriented Programming (OOP).
CO2 Describe the real world problems using object-oriented programming
concepts.
CO3 Develop the programs using the fundamental concepts of OOP.
CO4 Identify and use various techniques used in OOP.
CO5 Apply techniques used in OOP to solve the software design problems on a
given software project.
CO6 Demonstrate the learning on the course to solve the real life programming
problems.
Course Content
Unit-1: Review of Structured programming in C, Structured versus Object-Oriented Programming,
Principles of Object-Oriented Programming, Beginning with C++, Control Structures, Functions in
C++, Reference Variables, Default Parameters, Function Overloading, Inline Function, Const
Variables.
Unit-2: Classes, Member Functions, Objects, Static Data Members, Static Member Functions, Friend
Functions, Pointer to Members, Local classes, Constructors and Destructors of objects in C++,
Unit-3: Operator overloading and Type Conversions, Inheritance and its form, Multiple Inheritance in
C++, Function Overriding, Virtual Inheritance, Virtual Base Class .
Unit-4: Pointers, Early binding, late binding, Type of polymorphism, Virtual Functions, Abstract Class,
Virtual Destructor
Unit-5: Managing Console I/O Operations, File handling and Exception handling.
Unit-6: Templates, Function templates, Class templates, introduction to Standard Template Library
(STL), Sequence, Containers, Iterators

Teaching Methodology
The course will use the mixed technique of interactive lectures, tutorials, guided case studies, literature
survey, regular assignments and project work. Teaching in this course is designed to engage the students
in active and experiential learning by taking a problem solving and design-oriented approach with
special emphasis on real world applications.
In the lectures the fundamental theoretical concepts will be introduced and demonstrated through
examples and case studies. Discussion in lecture will be done using design problems which will be
implemented in laboratory individually in C++.

Evaluation Scheme

Evaluations Marks Remarks

T1 15 Marks (1 Hour)

T2 25 Marks (1.5 Hours)

T3 35 Marks(2 Hours)
2 or 3 Assignments to
Assignments 10 Marks
given
Quiz 5 Marks 2 or 3 quizzes

Tutorials 5 Marks

Attendance 5 Marks

Total 100 Marks

Text books

Text book1: Robert Lafore, Object oriented programming in C++, Waite Group.
Text book2: E Balagurusamy, “Object-Oriented Programming with C++”

References

1. Deitel and Deitel,“C++ How to program”, - Pearson Education.

2. Stroustrap B., the C++ Programming Language, Addison Wesley.
3. Lippman F. B., C++ Primer, Addison Wesley.
4. Prata S., C++ Primer Plus, Waite Group.
5. Parimala N., Object Orientation through C++, Macmillan India Ltd. 1999.
6. Pohl I., Object oriented Programming Using C++, Addison Wesley.
7. Grady Booch, James Rambaugh, Ivar Jacobson,“Unified Modelling Language user’s guide” ,
Addison Wesley Limited
Title of Course: Engineering Physics Lab-II Course Code: PH202
L-T-P Scheme: 0-0-2 Course Credit: 1

Learning Outcomes
Course Description
Outcome

CO1 Demonstrate ability to collect experimental data and understanding the working
procedures within the precautionary limits

CO2 Acquired the ability to analyze the experimental data and related errors in a reflective,
iterative and responsive way
CO3 Developed understanding of the basic concepts related to Modern Physics, Basic Solid
State Physics, Optics,
CO4 Acquired a first hand and independent experience of verifying the working principle of
solar cell
CO5 Appreciate the importance of the laboratory work culture and ethics that is intended to
impart features like regularity, continuity of self evaluation and honesty of reporting the
data

Experiments List

1. To determine the magnetic susceptibility of a paramagnetic, FeCl3 solution by Quinck’s tube

method.
2 To determine dispersive power of a prism using spectrometer.
3. To study the magnetostriction in metallic rod using Michelson-
Interferometer.
4. To determine the Planck’s constant using Photo electric effect.
5. To study the Hall effect in P type semi conductor and to determine
(i) Hall voltage and Hall coefficient
(ii) Number of charge carriers per unit volume
(iii) Hall angle and mobility
6. To study the variation of resistivity of a semiconductor with temperature and
to determine the band gap using Four-Probe method.

7. To study the presence of discrete energy levels in an atom by Franck Hertz

experiment.
8. Using solar cell Trainer (a) study voltage and current of a solar cell
(b) Voltage and current in series and parallel combinations (c) Draw power
curve to find maximum power point (MPP) and to obtain efficiency of a solar cell.
Title: Electrical Science Lab Code: EC203
L-T-P Scheme: 0-0-2 Credit: 1

Prerequisite: Student must have already registered for the course, “Physics Lab-I”

Objective:
1. The main aim of the lab is to familiarize with different types of electrical and electronic circuits
2. Identify their applications to the different electrical and electronic systems.
Learning Outcomes:
1. Completion of lab students will be able to understand the different techniques to simplify circuit
2. Two port networks and basic principles of different electronic devices and their characteristics.

Course Description
Outcome
CO1 Simplify complex network using Thevenin theorem and verify
it.State Superposition Theorem and verify.Perform and verify
Maximum Power Transfer Theorem.
CO2 To determine the Z parameters of the given two port network.
Calculate the Y parameters for the given two port network.
CO3 V-I characteristic of p-n junction diode
CO4 Design Clipper and Clamper Circuit.
CO5 Rectifier circuits
CO6 Transistor and their v-I characteristics

Course Content:
1. Simplify complex network using Thevenin theorem and verify it.
2. State Superposition Theorem and verify.
3. Perform and verify Maximum Power Transfer Theorem.
4. To determine the Z parameters of the given two port network.
5. Calculate the Y parameters for the given two port network.
6. Perform Clipper Circuit.
7. Design Clamper Circuit.
8. Half wave rectifier with and without filter circuit.
9. Full wave rectifier with and without filter circuit.
10. Transistor as an Amplifier.
11. Common Emitter v-i characteristic of n-p-n transistor.
12. Common base v-i characteristic of n-p-n transistor.

Unit I: Basic Electrical Circuit

Voltage Divider, Current Divider; Kichhoff’s Circuit Laws; Loop-Current Analysis, Mesh
Analysis; Node-Voltage Analysis; Choices of Method of Analysis. Source Transformation,
Combination of Sources; series and parallel combination of resistors.
Unit 2: Network Theorems (DC Circuits)
Superposition Theorem; Thevenin’s Theorem; Norton’s Theorem; Maximum Power Transfer
Theorem.
Unit 3: Two-Port Networks
Impedance, Admittance, Hybrid, Transmission Parameters; Equivalent Networks.

UNIT 4: Diodes and its Applications

Unidirectional property, PN-junction with no bias, with forward bias and with reverse bias, V-I
characteristics, Diode resistance (static and dynamic), Diode equation, Ideal diode, Circuit model of a
diode. Half-wave and full-wave (centre tap and bridge) rectifiers, PIV rating of diode, Performance of
half-wave and full-wave rectifiers, Shunt capacitor filter.
Clippers: Series and Parallel, Limiters, Clampers. Zener diode, Analysis of Zener voltage regulator.
LED, varactor diode .

UNIT 5: Transistor
BJT as an amplifier, CB and CE input and output characteristics.
Teaching Methodology:
In each experiment the practical is designed and analyzed on bread board with the help of physical
devices by each student and further checked and validated by faculty and lab staff.
Evaluation Scheme:
Exams Marks Coverage
P-1 15 Marks Based on Lab Exercises: 1-6
P-2 15 Marks Based on Lab Exercises: 6-12
Viva 20 Marks
Demonstration 20 Marks
Day-to-Day Work Lab Record 15 Marks 70 Marks
Attendance &
15 Marks
Discipline
Total 100 Marks

Learning Resources:
Tutorials sheets, lecture slides and handwritten notes on Electrical circuit, Electrical Science and Basic
Electronics (will be added from time to time): Digital copy will be available on the JUET server.
Text-Books:
1. D.C. Kulshreshtha, “Basic Electrical Engineering”, McGraw Hill Education, 2009.
 2. W.H. Hayt, J. E. Kemerlay & S.M. Durbin, “Engineering Circuit Analysis (Sixth Edition)”,
McGraw Hill, 2006.

3. R.C. Dorf & J.A. Svoboda, “Introduction to Electric Circuits”, John Wiley, 2004.

4. D.S. Chauhan & D.C. Kulshreshtha, ‘Electronics Engineering’, New Age, 2e, 2009.

5. D.C. Kulshreshtha, ‘Electronic Devices and Circuits’, New Age, 2e, 2006.

References:
1. Van Valkenburg, “Network Analysis”, Prentice-Hall India Ltd., 2001.

2. Abhijit Chakrabarti, Sudipta Nath, Chandan Kumar Chanda, “Basic Electrical Engineering”,
Tata McGraw Hill Publishing Co, 2008.

3. Vincent Del Toro, “Principles of Electrical Engineering”, Prentice Hall of India.

4. Kumar and Jain, ‘Electronic Devices and Circuits’, PHI, 2007.

5. Boylstad and Nashelsky, ‘Electronic Devices and Circuits’, PHI, 6e, 2001.

Web References:
1. https://www.electrical4u.com/electrical-engineering-objective-questions-mcq/

2. https://www.pdfdrive.com/basic-electric-circuit-analysis-books.html

3. https://lecturenotes.in/subject/842

Journals References:
1. Circuits, Systems, and Signal Processing (CSSP), Springer

2. Journal of Electrical & Electronic Systems

3. International Journal of Circuit Theory and Applications, Wiley

 Title of Course: Object Oriented Programming Lab Course Code: CS202
L-T-P Scheme: 0-0-2 Course Credit: 1

Pre-requisites
Students must have already registered for the course, “Software Development Fundamentals Lab”.

Objectives
To strengthen their problem solving ability by applying the characteristics of an object-oriented
approach and to introduce object oriented concepts in C++.
Learning Outcomes
CO1 Define basic concepts of Object-Oriented Programming (OOP).
CO2 Illustrate the key features available in OOP using C++.
CO3 Apply the concepts of OOP to solve different common problems.
CO4 Utilize the knowledge of OOP in solving programming problems.
CO5 Analyze the various concepts of OOP for their suitability on a given problem.
CO6 Design the systems, from concept to executable artefact, using object
oriented techniques.

Course Content
Unit-1: Structured versus Object-Oriented Programming, Principles of Object-Oriented Programming,
Beginning with C++, Control Structures, Functions in C++, Reference Variables, Default Parameters,
Function Overloading, Inline Function, Const Variables.

Unit-2: Classes, Member Functions, Objects, Static Data Members, Static Member Functions, Friend
Functions, Pointer to Members, Local classes, Constructors and Destructors of objects in C++,

Unit-3: Operator overloading and Type Conversions, Inheritance and its form, Multiple Inheritance in
C++, Function Overriding, Virtual Inheritance, Virtual Base Class .

Unit-4: Pointers, Early binding, late binding, Type of polymorphism, Virtual Functions, Abstract Class,
Virtual Destructor

Unit-5: Managing Console I/O Operations, File handling and Exception handling.

Unit-6: Templates, Function templates, Class templates, introduction to Standard Template Library
(STL), Sequence, Containers, Iterators

Laboratory work and project

The students shall be given regular lab assignments, which will allow them to practically apply the
concepts studied in the lecture Session. The lab assignments will be designed with focus on applying the
concepts learnt in object-oriented programming, Data structures in an integrated manner.
Evaluation Scheme

Evaluations Marks Remarks

P-1 15 Marks
P-2 15 Marks
Viva 20 Marks
Demonstration 20 Marks
Continuous
Lab Record 15 Marks
Evaluations
Discipline and
Punctuality and 15 Marks
Attendance
Total 100 Marks

Text book

Text Book1: Robert Lafore, Object oriented programming in C++, Waite Group
Text Book2: E Balagurusamy, “Object-Oriented Programming with C++”

References

1. Stroustrap B., the C++ Programming Language, Addison Wesley.

2. Lippman F. B., C++ Primer, Addison Wesley.
3. Prata S., C++ Primer Plus, Waite Group.
4. Parimala N., Object Orientation through C++, Macmillan India Ltd. 1999.
5. Pohl I., Object oriented Programming Using C++, Addison Wesley.
6. Grady Booch, James Rambaugh, Ivar Jacobson,“Unified Modelling Language user’s guide” ,
Addison Wesley Limited
Title: Engineering Drawing & Design Lab Code: ME203
L-T-P scheme: 0-0-3 Credits: 1.5

OBJECTIVE

[1] Enables students to learn the concepts of graphic communication, their role in sanitary
construction.
[2] Make familiar with different drawing equipment, technical standards and procedures for
construction of geometric figures.
[3] Equipped with the skill that enables them to convert pictorial to orthogonal representations.

Learning Outcomes:
Course Description
Outcome
CO1 Outline the objectives of scale and develop the imagination and mental
visualization capabilities for correlating the geometrical details of objects.
CO2 To develop the constructional ability for a different curve.
CO3 To Describe BIS rules for orthogonal projection and understand the fundamental
concept of orthogonal projection for point, line, plane and solids.
CO4 Understand and apply orthogonal projection for solids, section and intersection of
solid objects/structures
CO5 To apply the skill of development of surfaces of three dimensional objects for
evaluation of black size of the components.
CO6 Demonstrate computer aided drafting tools and techniques using CAD software’s

Course Content:
Unit-1: Study and construction of lines, lettering, dimensioning, plane scales, diagonal scales,
construction of different methods used for the construction of conic curves.
Unit-2: Study and construction of geometrical construction, cycloidal curves, involutes and helix etc.
Unit-3: Orthogonal projection of point in all possible positions, Study and construction of projection of
line and its applications (inclined to both planes), and projection of planes (inclined to both planes).
Unit-4: Study and construction of projection of solids (right circular cone, prism, pyramid and
cylinders), and true shape of sections,
Unit-5: Study and construction of oblique projection and development of surface, isometric view using
orthogonal projection on isometric scales.
Unit-6: Introduction to basic and editing command of CAD software, 2-D drafting, surface modeling,
and 3-D geometrical model.

Teaching Methodology:
This course is introduced to build the imagination and established the correlation between the real object
and engineering drawing and CAD developed by the design engineers and the requirement of the
production engineers of the different units.
 Evaluation Scheme:

Exams Marks Coverage

P-1 15 Marks Based on Lab Exercises: 1-7
P-2 15 Marks Based on Lab Exercises: 8-14
Day-to-Day Work Viva 20 Marks 70 Marks
Demonstration 20 Marks
Lab Record 15 Marks
Attendance & 15 Marks
Discipline
Total 100 Marks

Learning Resources:
The study material of engineering drawing & design lab (will be added time to time): Digital copy will
be available on the JUET server.

Text Book:
1. Bhatt, N.D., Engineering Drawing,

Reference Books:
1. Gill, PS, A Text Book of Engineering Drawing (Geometrical Drawing)
2. Dhananjay A J, Engineering Drawing with an introduction to Auto CAD, Mc Graw Hill
 Course Description
3rd Semester:
Title: Techniques for Decision Making Code: HS103
L-T-P scheme: 2-1-0 Credit: 3

Prerequisite: None

Objectives:
1. To use basic techniques of inferential data analysis, quality control, and regression modeling;
2. To analyze a set of data, to reach a conclusion based on these analyses, and to make and defend a
recommended course of action;
3. To be well-equipped to take courses in Marketing, Investments, Accounting, Finance, and
Operations Management that require proficiency in statistical methods.

Learning Outcomes:

Course Description
Outcome
Outline various concepts of techniques for decision making with respect to the
CO1 needs of modern business management.
Describe the real world problems using basic techniques of descriptive and
CO2
inferential data analysis and business forecasting.
CO3 Identify and use various index numbers used in business decision making.
Apply decision making techniques to reach a conclusion based on the data
CO4
analysis, and to make and defend a recommended course of action.
CO5 Deployment and proficiency in statistical methods.
Develop the understanding to analyze a set of data using correlation analysis
CO6
and regression analysis.

Course Content:
Unit-1: Collection of data and Presentation of data: Classification of data, Secondary data, Primary
data, Designing of questionnaire, Unstructured and structured questionnaire, Tabulation of data,
Charting of data.
Unit-2: Business Forecasting: Introduction, steps in forecasting, good forecasting, Time series
forecasting, secular trend, seasonal variations, cyclical variations.
Unit-3: Index numbers: Uses, classification, problems, Methods of constructing index numbers,
unweighted index numbers, Consumer Price index numbers.
Unit-4: Statistical Decision making : Decision making under certainity, Risk , uncertainty and
conflict, Zero sum game, Prisoner’s dilemma , Payoff Table, Maximin and minimax strategy.
Unit-5: Correlation Analysis and Regression analysis: Significance of the study of correlation,
Correlation and causation, Karl Pearson’s coefficient of correlation, Rank correlation, Method of
 least squares, Difference between correlation and regression, Regression lines and regression
equation, Regression equation of Y on X and regression equation of X on Y.

Teaching Methodology:
The course “Techniques for Decision Making” is introduced to explain the basic concepts in
statistics that have wide applicability in business decision making. As such, the focus will be more
practical than theoretical. Because statistical analysis informs the judgment of the ultimate decision-
maker—rather than replaces it—we will cover some key conceptual underpinnings of statistical
analysis to insure that the students understand its proper usage. Statistics is about improved
decision-making, which can be achieved through a thorough understanding of the data. We want to
leave our pre-conceived notions at the door, and let the data tell us what is going on in a situation.
The analytical techniques should provide valuable information to decision-makers. As such, it plays
an important role in management decision processes. The course will be taught with the aid of
lectures, tutorials, handouts, case studies, and problem-based learning.

Evaluation Scheme:
Exams Marks Coverage
Test-1 15 Marks Based on Unit-1 & Unit-2
Based on Unit-3 & Unit-4 and around 30% from
Test-2 25 Marks
coverage of Test-1
Based on Unit-5 and around 30% from coverage
Test-3 35 Marks
of Test-2
Assignment 10 Marks
Tutorials 5 Marks
Quiz 5 Marks
Attendance 5 Marks
Total 100 Marks

Learning Resources:
Lectures, tutorials and e-books on Techniques for Decision Making (will be added from time to
time): Digital copy will be available on the JUET server.
Text Book:
1. “Business Statistics”; S.P. Gupta & M.P. Gupta, S. Chand Publishing, New Delhi, 2013.

Reference Books/Material:
1. “Statistics for Business & Economics”; Anderson, Thomson Learning, Bombay.
2. “Quantitative Methods in Business”; Anderson, Thomson Learning, Bombay.
3. “Business Statistics”; R.S. Bhardwaj, Excel Books.
4. “Statistics for Management”; Levin & Rubin, Prentice Hall of India, New Delhi.
5. “Two Person Game Theory”; A. Rapport & Anne Arbric, The University of Michigan Press,
1966.
Title of Course: Data Structures Course Code: CS103
L-T-P Scheme: 3-1-0 Credits: 4

Scope and Objectives:

This course develop problem solving ability using programming, develop ability to express solutions to
problems clearly and precisely, develop ability to design and analyze algorithms, introduce with
fundamental data structures, develop ability to design and evaluate abstract data types and data structures.

Learning Outcome:

The students shall acquire the generic skills to design and implement data structures and related algorithms
for a broad-based set of computing problems.

Course Outcome Description

CO1 List various types of data structures with respect to their requirements in
different fields.
CO2 Describe the various methods to evaluate the algorithms.
CO3 Develop algorithms based on linear data structures
CO4 Identify the suitability of the data structures as per the requirements.
CO5 Apply data structures to solve the software design problems.
CO6 Demonstrate the learning on the course to solve the real life programming
problems.

This course is intended to provide a thorough introduction to the use of data structures in programming.
This course will cover the necessary mathematical background, but will assume the required programming
experience.

Course Contents:
UNIT 1: Introduction to Data Structures, Algorithm and Complexity
Data structure overview, need of data structure and how to select relevant data structure for given problem,
basic C data types and ADT.
Algorithm overview and its properties, problem analysis and construction of algorithm, difference
between algorithm, program and software, algorithm analysis and complexity, asymptotic notations to
represent the time complexity, Software Development Life Cycle (SDLC) phase
UNIT 2: Array
Overview, memory representation of 1D and 2D array, sparse matrix, operation supported by an array
Part 1: Searching
Linear search with illustration, analysis of linear search, binary search (iterative) and its analysis, binary
search (recursive) and its analysis using recurrence relation, recurrence relation
Part 2: Sorting
Types of sorting algorithms, bubble sort, selection sort, insertion sort, quick sort, merge sort
UNIT 3: Linked List
Overview, types of linked list, linear linked list – overview, traversing, insertion, deletion, searching and
reverse, doubly linked list – overview, traversing, insertion, deletion, circular linked list – overview, header
linked list, applications of linked list
UNIT 4: Stack
Overview, stack implementation using stack and linked list, basic operations on stack using array and
linked list – push, pop, dispose applications of stack – evaluation of mathematical expression, conversion
of expression from one form to another (Polish Notation), Tower of Hanoi problem
UNIT 5: Queue
Overview, basic operations on queue – enqueue, dequeue, implementation of queue using array and linked
list, types of queue - linear queue, circular queue, deque, priority queue, applications
UNIT 6: Tree
Tree definition and its terminology, representation of graph using array and linked list, tree traversals –
preorder, inorder and postorder, binary search tree (BST) with insertion, deletion and searching operations,
extended binary tree and its application in Huffman tree, threaded binary tree
UNIT 7: Graph
Introduction to graph, types of graph, traversal algorithms in graph – breadth first search, depth first search,
spanning tree, minimum cost spanning tree - Kruskal’s, Prim’s.

Evaluation Scheme:

Component & Nature Duration Marks / Weightage

T1 1 hr 15
T2 1&1/2 hrs 25
T3 2hrs 35
Tutorials 05
Attendance 05
Quiz 05
Assignments 10
Total 100

Text Book::
T1: Sartaj Sahni, “Fundamentals of Data Structures”, Tata Mc Graw Hill, New York
T2: Seymour Lipschutz., “Data Structures with C”, Schaum's Outline Series
T3: Narasimha Karumanchi, “Data Structures and Algorithms” Made Easy

Reference Books:
R1: Corman et al: Introduction to Computer Algorithms
R2: Langsam, Augestein, Tenenbaum: Data Structures using C and C++
R3: Weiss: Data Structures and Algorithm Analysis in C/C++
R4: Samir K. Bandyopadhyay,” Data Structures using C”
R5: Hopcraft, Ullman: Data Structures and Algorithms
Title: Theory of Computation Code: CS110
L-T-P scheme: 3-0-0 Credit: 3

Prerequisite:
Students must have already studied for the course Set algebra, elementary
formal logic, constructing proofs, recurrence relations.
Objective:
1. To give an overview of the theoretical foundations of computer science from the
perspective of formal languages
2. To illustrate finite state machines to solve problems in computing
3. To explain the hierarchy of problems arising in the computer sciences.
4. To familiarize Regular grammars, context frees grammar.
Learning Outcomes:
Course Outcome Description
Students will demonstrate knowledge of basic mathematical models of
CO1
computation and describe how they relate to formal languages.
CO2 To Design Finite Automata’s for different Regular Expressions and Languages
To Construct grammar for various languages and applying normal forms and
CO3
push down automata
CO4 To solve various problems of Turing Machines and types of TM

Course Content:
UNIT – I
Mathematical Concepts: Review definitions and notations for sets, relations and functions. Basic
concepts and definitions Set operations; partition of a set, Equivalence relations; Properties on relation on
set; Proving Equivalences about Sets. Central concepts of Automata Theory.

UNIT – II
FINITE AUTOMATA (FA): Introduction, Deterministic Finite Automata (DFA) -Formal definition,
simpler notations (state transition diagram, transition table), language of a DFA. Nondeterministic
Finite Automata (NFA)- Definition of NFA, language of an NFA, Equivalence of Deterministic and
Nondeterministic Finite Automata, Applications of Finite Automata, Finite Automata with Epsilon
Transitions, Eliminating Epsilon transitions, Minimization of Deterministic Finite Automata, Finite
automata with output (Moore and Mealy machines) and Inter conversion.

UNIT - III
REGULAR EXPRESSIONS (RE): Introduction, Identities of Regular Expressions, Finite Automata
and Regular Expressions- Converting from DFA’s to Regular Expressions, Converting Regular
Expressions to Automata, applications of Regular Expressions.
REGULAR GRAMMARS: Definition, regular grammars and FA, FA for regular grammar, Regular
grammar for FA. Proving languages to be non-regular -Pumping lemma, applications, Closure
properties of regular languages.

UNIT - IV
CONTEXT FREE GRAMMER (CFG): Derivation Trees, Sentential Forms, Rightmost and
Leftmost derivations of Strings. Ambiguity in CFG’s, Minimization of CFG’s, CNF, GNF, Pumping
Lemma for CFL’s, Enumeration of Properties of CFL (Proof’s omitted).

UNIT – V
PUSHDOWN AUTOMATA: Definition, Model, Acceptance of CFL, Acceptance by Final State and
Acceptance by Empty stack and its Equivalence, Equivalence of CFG and PDA.

UNIT VI
TURING MACHINES (TM): Formal definition and behaviour, Languages of a TM, TM as accepters,
and TM as a computer of integer functions, Types of TMs.
RECURSIVE AND RECURSIVELY ENUMERABLE LANGUAGES (REL): Properties of
recursive and recursively enumerable languages, Universal Turing machine, The Halting problem,
Undecidable problems about TMs. Context sensitive language and linear bounded automata (LBA),
Chomsky hierarchy, Decidability.

Teaching Methodology:
Teaching in this course is designed to engage the students in active and experimental learning by taking a
problem solving and design oriented approach with special emphasis on real world applications. Students
are expected to carry out lot of design and programming.
Evaluation Scheme:
Exams Marks Coverage
Test-1 15 Marks Based on Unit-1, Unit-2
Based on Unit-3 & Unit-4 and around 30%
Test-2 25 Marks
from coverage of Test-1
Based on Unit-5 to Unit-6 and around 30%
Test-3 35 Marks
from coverage of Test-2
Assignment 10 Marks
Tutorials 5 Marks
Quiz 5 Marks
Attendance 5 Marks
Total 100 Marks

Learning Resources:
Tutorials and lecture slides on Theory of Computation (will be added from time to time): Digital
copy will be available on the JUET server.
Text Books:
1. K. L. P Mishra, N. Chandrashekaran (2003), Theory of Computer Science-Automata
Languages and Computation, 2nd edition, Prentice Hall of India, India.
2. John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman (2007), Introduction to Automata
Theory Languages and Computation, 3rdedition, Pearson Education, India.
Reference Books:
1. Papadimitriou, Elements of the Theory of Computation, Prentice-Hall, 1998
2. Peter Dehning, Jack B. Dennis, “Machines, Languages and Computation”, Second Edition,
Prentice-Hall, 1978
3. Harry R. Lewis, Christos H. Papadimitriou, "Elements of the theory of computation", Second
Edition, Prentice-Hall, 1998
Title of Course: Database Systems Course Code: CS104
L-T-P Scheme: 3-1-0 Course Credits: 4

Objectives: To develop the ability to design, implement and manipulate databases as well as to build
Database management systems
Learning Outcome:
1. Ability to build normalized data bases.
2. Ability to design systems by using ER Modeling.
3. Ability to develop skills of writing applications by using SQL.
4. Ability to understand query optimization techniques.
5. Understanding of transaction processing.
6. Ability to handle recovery and concurrency issues

Course Description
Outcome
CO1 Introduction various types of database systems with respect to their
features and characteristics and requirements in different fields.
CO2 Describe the various data definition, manipulation and various
modifiers queries for database design. Characteristics
CO3 Develop algorithms based on linear data structures
CO4 Develop the database using relational database query, Identify the
suitable of the data structures as per the requirements.
CO5 Develop the normalized database with features of transaction,
concurrency and recovery control
CO6 Demonstrate the learning on the course to deployed the database
systems basis of the real life database problems.

Course Contents:
Introduction to Databases, Database Environment, Relational Model, Relational Algebra, SQL: Data
Manipulation, Data Definition, And Commercial RDMS: MS-Access/MySQL, PL/SQL, ER Modeling:
Entity type, Attributes, Relation types, Notations, Extended ER Features, Normalisation and building
normalized databases & Data Dependencies, Case Study, Database Connectivity: Python MySQL
Connectivity, Transactions, Concurrency, Recovery & Security, Query Processing & Optimization.

Text Book
1. “Database system concepts”, Henry F Korth, Abraham Silberschatz, S. Sudurshan, McGraw-Hill, 4th
Edition.
References
1. “An Introduction to Database Systems” Bipin. C. Desai. Revised Edition 2006.
2. "Fundamentals of Database Systems", Elmasri, Navathe, Pearson Education, IVth Edition.
3. “An Introduction to Database Systems”, C. J. Date, Pearson Education.
4. “Introduction to Data Base Management”, Naveen Prakash, Tata McGraw Hill.
5. “Database Management Systems” , Ramakrishna, Gehrke; McGraw-Hill.
6. “Database Systems: A Practical Approach to design, Implementation and Management”, Thomas
Connolly, Carolyn Begg; Third Edition, Pearson Education.
7. “A first course in Database Systems”, Jeffrey D. Ullman, Jennifer Windon, Pearson Education
8. “Data Management: databases and organization”, Richard T. Watson, Wiley Publication.
9. “Data Modeling Essentials”, Graeme C. Simxion, Dreamtech Publications.
10. MS-ACCESS Projects “Oracle 8i manuals”.
Title: Environnemental Science Code: GE101
L-T-P Scheme: 2-0-0 Credit: 0

Prerequisite: The students must be aware of basic Environmental Science upto class 12th. Basic
knowledge of Environmental Science helps them to correlate in various division of Engineering during this
course.

Objective:
The purpose behind this course is to make the students familiar with Environment (surrounding) and to
understand the significance/importance of natural resource, biodiversity, environment pollution and impact
of intervention of human being in the Ecosystem. This course is mandatory for all branches of the
Engineering and Sciences.

Course Learning Outcomes:

Course Description
Outcome
CO1 The outline, outcomes and attributes provide students with learning experiences that help
in learning the significance and importance of environment in their life.

CO2 Describe the real world problems, challenges with the suitable case study based on
conservation (natural resource and biodiversity), ecosystem, socio-economic development
and remedial measure of the various pollutions (air, water, soil, noise and radiation).

CO3 Develop in students the ability to apply the knowledge and skills they have acquired to
the solution of specific theoretical and applied problems in their surrounding (the
Environment).

CO4 Identify and use of various techniques for solving the Environmental Problems.

CO5 Apply filed visit and justification by using various analytical techniques.

CO6 Demonstrate students with the knowledge and skill base that would enable them to
undertake further studies in the Environmental Science and related multidisciplinary areas
that involve Environmental Science and help to develop a range of generic skills that are
relevant to wage employment, self-employment and entrepreneurship.
Modules Description No. of
lectures
Unit 1: Introduction to Environmental Science: Multidisciplinary nature of 2
environmental science; components of environment –atmosphere,
hydrosphere, lithosphere and biosphere. Scope and importance; Concept of
sustainability and sustainable development.
Unit 2: Ecosystems: What is an ecosystem? Structure and function of ecosystem; 4
Energy flow in an ecosystem: food chain, food web and ecological
succession. Case studies of the
following ecosystems:
a) Forest ecosystem
b) Grassland ecosystem
c) Desert ecosystem
d) Aquatic ecosystems (ponds, streams, lakes, rivers, oceans, estuaries)
Unit 3: Natural Resources: Renewable and Non-renewable Resources 5
• Land Resources and land use change; Land degradation, soil erosion and
desertification.
• Deforestation: Causes and impacts due to mining, dam building on
environment, forests, biodiversity and tribal populations.
• Water: Use and over-exploitation of surface and ground water, floods,
droughts, conflicts over water (international & inter-state).
• Heating of earth and circulation of air; air mass formation and precipitation.
• Energy resources: Renewable and non-renewable energy sources, use of
alternate energy sources, growing energy needs, case studies.
Unit 4: Biodiversity and its conservation: Levels of biological diversity: genetic, 4
species and ecosystem diversity; Biogeography zones of India; Biodiversity
patterns and global biodiversity hot spots. • India as a mega-biodiversity
nation; Endangered and endemic species of India. • Threats to biodiversity:
habitat loss, poaching of wildlife, man-wildlife conflicts, biological
invasions; Conservation of biodiversity: In-situ and Ex-situ
Conservation of biodiversity. • Ecosystem and biodiversity services:
Ecological, economic, social, ethical, aesthetic and Informational value.
Unit 5: Environmental Pollution: Environmental pollution: types, causes, effects and 5
controls; Air, water, soil, chemical and noise pollution. • Nuclear hazards and
human health risks. • Solid waste management: Control measures of urban
and industrial waste. • Pollution case studies.
Unit 6: Environmental Policies & Practices: Climate change, global warming, ozone 4
layer depletion, acid rain and impacts on human communities and
agriculture.• Environment Laws : Environment Protection Act; Air
(Prevention & Control of Pollution) Act; Water (Prevention and control of
Pollution) Act; Wildlife Protection Act; Forest Conservation Act;
International agreements; Montreal and Kyoto protocols and conservation on
Biological Diversity (CBD). The Chemical Weapons Convention (CWC).
• Nature reserves, tribal population and rights, and human, wildlife conflicts
in Indian context.
Unit 7: Human Communities and the Environment Human population and growth: 4
Impacts on environment, human health and welfares.
• Carbon foot-print.
• Resettlement and rehabilitation of project affected persons; case studies.
• Disaster management: floods, earthquakes, cyclones and landslides.
• Environmental movements: Chipko, Silent valley, Bishnios of Rajasthan.
• Environmental ethics: Role of Indian and other religions and cultures in
environmental conservation.
• Environmental communication and public awareness, case studies (e.g.,
CNG
vehicles in Delhi).
Unit 8: Field Work: Visit to a local area to document assets-river / forest / grassland 4
/hill / mountain. polluted sites(Urban, rural ,industrial, agriculture), plants,
insects, bird, Ecosystem (pond, river, hill slopes etc)
Total 32

Teaching Methodology:
The core module Syllabus for Environment Science includes class room teaching and Field Work. The
syllabus is divided into eight units covering lectures. The first seven units will cover 28 lectures, which are
class room based to enhance knowledge skills and attitude to environment. Unit eight is based on field
activities which will be covered in 4 lecture hours and would provide student firsthand knowledge on
various local environmental aspects. Field experience is one of the most effective learning tools for
environmental concerns. This moves out of the scope of the text book mode of teaching into the realm of
real learning in the field, where the teacher merely acts as a catalyst to interpret what the student observes
or discovers in his/her own environment. Field studies are as essential as class work and form an
irreplaceable synergistic tool in the entire learning process. Course material provided by UGC for class
room teaching and field activities is utilized.

Evaluation Scheme:
Exams Marks Coverage
Test-1 15 Marks Based on Unit-1 Unit 2 and Unit-3
Based on Unit-4 & Unit-5 (70 %) and around
Test-2 25 Marks
30% from coverage of Test-1
Based on Unit-6 to Unit-7 and around 30%
Test-3 35 Marks
from coverage of Test-1 and Text-2
Assignment 10 Marks
Tutorials 5 Marks
Quiz 5 Marks
Attendance 5 Marks
Total 100 Marks
Learning Resources:
Tutorials and lecture slides on Web Development (will be added from time to time): Digital copy will be
available on the JUET server.
Text Book
1. Bharucha Erach, 2003. The Biodiversity of India, Mapin Publishing Pvt. Ltd, Ahmadabad –
380013, India.
2. De Anil Kumar, Environmental Chemistry, Wiley Eastern Ltd, 2007.
3. Agarwal KC, 2001. Environmental Biology, Nidhi Publishers Ltd. Bikaner.
Reference Book
1. Brunner RC, 1989, Hazardous Waste Incineration, McGraw Hill Inc. 480pgs.
2. Clark R B, Marine Pollution, Clanderson Press, Oxford (TB).2001.
3. Cunningham WP, Cooper TH, Gorhani E & Hepworth MT, 2001. Environmental Encyclopedia,
Jaico Publishing House, Mumbai, 1196 pgs.
4. Gleick HP, 1993. Water in Crisis, Pacific Institute for Studies in Development, Environment and
Security. Stockholm Environmental Institute, Oxford University Press, 473pgs.
5. Heywood VH, and Watson RT, 1995. Global Biodiversity Assessment. Cambridge University Press
1140pgs.
6. Jadhav H and Bhosale VM, 1995. Environmental Protection and Laws. Himalaya Publishing
House, Delhi 284pgs.
7. Mckinney ML and Schoch RM, 1996. Environmental Science Systems and Solutions. Web
enhanced edition, 639pgs.
Title of Course: Data Structures Lab Course Code: CS203
L-T-P Scheme: 0-0-2 Credits: 1

Scope and Objectives:

This course develop problem solving ability using programming, develop ability to express solutions to
problems clearly and precisely, develop ability to design and analyze algorithms, introduce with
fundamental data structures, develop ability to design and evaluate abstract data types and data structures.

Learning Outcome:

The students shall acquire the generic skills to design and implement data structures and related algorithms
for a broad-based set of computing problems

CO1 Define basic operations on linear data structures

CO2 Illustrate the efficiency of a data structures in terms of time and space
complexity.
CO3 Apply the data structures solve the searching and sorting problems.
CO4 Utilize the knowledge of non-linear data structures in solving programming
problems.
CO5 Analyze the data structures for their suitability on a given problem.
CO6 Design the systems, from concept to executable artefact using data structures
techniques.

Course Description:

This course is intended to provide a thorough introduction to the use of data structures in programming.
This course will cover the necessary mathematical background, but will assume the required programming
experience.

Course Contents:

UNIT 1: Introduction to Data Structures, Algorithm and Complexity

Data structure overview, need of data structure and how to select relevant data structure for given problem,
basic C data types and ADT.
Algorithm overview and its properties, problem analysis and construction of algorithm, difference
between algorithm, program and software, algorithm analysis and complexity, asymptotic notations to
represent the time complexity, Software Development Life Cycle (SDLC) phase

UNIT 2: Array
Overview, memory representation of 1D and 2D array, sparse matrix, operation supported by an array
Part 1: Searching
Linear search with illustration, analysis of linear search, binary search (iterative) and its analysis, binary
search (recursive) and its analysis using recurrence relation, recurrence relation
Part 2: Sorting
Types of sorting algorithms, bubble sort, selection sort, insertion sort, quick sort, merge sort

UNIT 3: Linked List

Overview, types of linked list, linear linked list – overview, traversing, insertion, deletion, searching and
reverse, doubly linked list – overview, traversing, insertion, deletion, circular linked list – overview, header
linked list, applications of linked list

UNIT 4: Stack
Overview, stack implementation using stack and linked list, basic operations on stack using array and
linked list – push, pop, dispose applications of stack – evaluation of mathematical expression, conversion
of expression from one form to another (Polish Notation), Tower of Hanoi problem

UNIT 5: Queue
Overview, basic operations on queue – enqueue, dequeue, implementation of queue using array and linked
list, types of queue - linear queue, circular queue, deque, priority queue, applications

UNIT 6: Tree
Tree definition and its terminology, representation of graph using array and linked list, tree traversals –
preorder, inorder and postorder, binary search tree (BST) with insertion, deletion and searching operations,
extended binary tree and its application in Huffman tree, threaded binary tree

UNIT 7: Graph
Introduction to graph, types of graph, traversal algorithms in graph – breadth first search, depth first search,
spanning tree, minimum cost spanning tree - Kruskal’s, Prim’s.
Text Book:
T1: Sartaj Sahni, “Fundamentals of Data Structures”, Tata Mc Graw Hill, New York
T2: Seymour Lipschutz., “Data Structures with C”, Schaum's Outline Series
T3: Narasimha Karumanchi, “Data Structures and Algorithms” Made Easy

Reference Books:
R1: Corman et al: Introduction to Computer Algorithms
R2: Langsam, Augestein, Tenenbaum: Data Structures using C and C++
R3: Weiss: Data Structures and Algorithm Analysis in C/C++
R4: Samir K. Bandyopadhyay,” Data Structures using C”
R5: Hopcraft, Ullman: Data Structures and Algorithms
Evaluation Scheme:

Component & Nature Marks

Lab work 40
Lab record 15
Mid sem lab –Viva/Test 15
End sem lab – Viva/Test 15
Attendance & discipline in lab 15
Total 100
Title of Course: Database Systems Lab Course Code: CI204
L-T-P Scheme: 0-0-2 Course Credit: 1

Objectives: To develop the ability to design, implement and manipulate databases as well as to build
Database management systems.
Learning Outcome
1. Ability to design systems by using ER Modeling.
2. Ability to develop skills of writing applications by using SQL.
3. Ability to understand query optimization techniques and transaction processing.

CO1 Define basic requirement and operations of file based and database systems.
CO2 Illustrate the relational database design using data definition, data manipulation queries.
CO3 Develop the database using relational database query, Identify the suitable of the data
structures as per the requirements.
CO4 Utilize the knowledge of structured query language to develop and deploy the database for
real life based problems.
CO5 Develop the normalize database for their suitability on a given problem.
CO6 Design the database systems, from concept to executable transaction, concurrency and
recovery control using the real time based problems in group project based task .
Course Contents:
⮚ SQL queries for the creation of tables and insertion of values into tables.
⮚ SQL queries for viewing all data and specific data corresponding to a particular row or column in a
table.
⮚ SQL queries for the updation, deletion and dropping of tables.
⮚ SQL queries for aggregation, range finding etc on the tables.
⮚ SQL queries for renaming, truncating and destroying the tables.
⮚ SQL queries for the use of not null, group by, having clause.
⮚ SQL queries for the computation done on the table data.
⮚ Exercise on nested SQL queries and sub queries.
⮚ Use of cursors, triggers, functions and writing pl/sql block.
⮚ A brief idea about oracle report builder.
Evaluation scheme:
Exams Marks Coverage
P-1 15 Marks Based on Lab Exercises: 1-7
P-2 15 Marks Based on Lab Exercises: 8-14
Viva 20 Marks
Demonstration 20 Marks
Day-to-Day Work 70 Marks
Lab Record 15 Marks
Attendance & Discipline 15 Marks
Total 100 Marks

Text Book
1. SQL, PL/SQL the Programming Language of Oracle, Ivan Bayross, 3rd edition.
Title of Course: UNIX Programming Lab Course Code: CSXXX
L-T-P Scheme: 0-0-2 Course Credit: 1

Objectives: This course introduces basic understanding of UNIX OS, UNIX commands and File system
and to familiarize students with the Linux environment. To make student learn fundamentals of shell
scripting and shell programming. Emphases are on making student familiar with UNIX environment and
issues related to it.
Learning Outcome

CO1 Understand various UNIX commands on a standard UNIX/LINUX Operating system

CO2 Illustrate C / C++ programs on UNIX.
CO3 Develop and do shell programming on UNIX OS.
CO4 Utilize the knowledge to handle UNIX system calls

Course Contents:
⮚ Introduction to Unix Operating System and comparing it with Windows OS. Overview to Open
Source Software. Writing and studying about how to execute C program in UNIX environment
using GCC compiler along with phases of compilation. Executing simple Hello World C program
in UNIX environment using ed / nano / pico editor.
⮚ Working with the vi editor: Creating and editing a text file with the vi text editor using the standard
vi editor commands
⮚ UNIX for Beginners: Getting hands-on on basic UNIX commands
⮚ Some more UNIX commands: Working with directories, input-output redirection, Pipes, Processes
⮚ The UNIX file system
⮚ Using the Shell
⮚ Working with filters: grep, sed and awk
⮚ UNIX Shell Programming
⮚ Programming with standard I/O
⮚ UNIX Shell Call
Evaluation scheme:
Exams Marks Coverage
P-1 15 Marks Based on Lab Exercises: 1-7
P-2 15 Marks Based on Lab Exercises: 8-14
Viva 20 Marks
Demonstration 20 Marks
Day-to-Day Work 70 Marks
Lab Record 15 Marks
Attendance & Discipline 15 Marks
Total 100 Marks

Text Book
1. Brian W. Kernighan and Rob Pike, “The UNIX Programming Environment” Prentice Hall India
2. Sumitabha Das, “UNIX: Concepts and Applications” Tata McGraw Hill (Latest Edition)
3. Yashwant Kanetkar, “UNIX Shell Programming” BPB Publications (First Edition)
4. Jerry Peek and others, “Unix Power Tools” O’Reilly Publishers
Title of Course: Advance Programming Lab-I Course Code: CS206
L-T-P scheme: 0-0-2 Course Credits: 1

Prerequisite: No explicit prerequisite course work is required, but students are expected to have a
fundamental understanding of basic computer principles and previous experience using a personal
computer.

Objective: To emphasize object-oriented programming concepts and the design of algorithms and related
data structures. Problem decomposition and principles of software engineering are stressed throughout the
course. Advance aspects of programming may be taken care off through Python.
Learning Outcomes:

Course
Description
Outcome
CO1 Installation and understanding features of Python.
CO2 Describe Python data types to handle programming problems
CO3 Develop understanding looping to handle new data types
CO4 Identify appropriate methods to solve challenging problems.
CO5 Apply programming knowledge to solve real world problems in the form of Project

Course Contents:
An Introduction to Python: Introductory Remarks about Python, Strengths and Weaknesses, A Brief
History of Python, Python Versions, Installing Python, Environment Variables, Executing Python from the
Command Line, IDLE, Editing Python Files, Getting Help, Dynamic Types, Python Reserved Words,
Naming Conventions.

Basic Python Syntax: Introduction, Basic Syntax, Comments, String Values, String Operations,
The format Method, String Slices, String Operators, Numeric Data Types, Conversions, Simple Input and
Output, The print Function.

Language Components: Introduction, Control Flow and Syntax, Indenting, The if Statement, Relational
Operators, Logical Operators, True or False, Bit Wise Operators, The while Loop, break and continue,
The for Loop.

Collections: Introduction, Lists, Tuples, Sets, Dictionaries, Sorting Dictionaries, Copying Collections,
Summary.

Functions: Introduction, Defining Your Own Functions, Parameters, Function Documentation, Keyword
and Optional Parameters, Passing Collections to a Function, Variable Number of Arguments, Scope
Functions- “First Class Citizens”, Passing Functions to a Function, Mapping Functions in a Dictionary,
Lambda, Closures.

Exceptions: Errors, Run Time Errors, The Exception Model, Exception Hierarchy, Handling Multiple,
Exceptions, raise, assert, Writing Your Own Exception Classes.
Classes in Python: Classes in Python, Principles of Object Orientation, Creating Classes, Instance
Methods, File Organization, Special Methods, Class Variables, Inheritance, Polymorphism, Type
Identification, Custom Exception Classes, Class Documentation-pydoc.

GUI in Python: Introduction, Base window, Widgets, Functions, Lambda Functions, Geometry manager,
Sqlite3 Backend Connectivity, Handling images.

Project: Based on Learning in this course with database connectivity.

Text Book
5. Programming Python /Mark Lutz.
Reference Books
1. Think Python / Allen B Downey
2. Python 101 / Dave Kuhlman

Evaluation scheme:

Exams Marks Coverage

P-1 15 Marks Based on Lab Exercises: 1-7
P-2 15 Marks Based on Lab Exercises: 8-14
Viva 20 Marks
Demonstration 20 Marks
Day-to-Day Work 70 Marks
Lab Record 15 Marks
Attendance & Discipline 15 Marks
Total 100 Marks
 Course Description
4th Semester:

Title of Course: Software Engineering Course Code CS105

L-T-P Scheme: 3-0-0 Credits: 3

Pre-requisite: Good Knowledge of Computer Programming

Post Course:
Object Oriented Software Engineering, Software Quality Management Objective: To engineer good
quality software from its specification

Learning Outcomes
Software Engineering
Course Outcome Description
CO1 Outline various software models with respect to their needs of the customer
requirement and concepts of some modeling language.
CO2 Describe the real world problems using software engineering concepts and tools.
CO3 Develop the software design to meet customer expectations using modeling language.
CO4 Identify and use various cost estimation techniques used in software engineering
project management.
CO5 Apply verification and validation techniques on a given software project.
CO6 Demonstrate deployment and basic maintenance skills.

Course Outline:
Interactive Systems, Usability, Introduction to software engineering, Software process models, PSP, TSP
Requirement Engineering: Requirement Elicitation, Analysis, Specification, SRS, Formal system
development techniques, Analysis and Modeling: Data modeling, Functional modeling, Software
Architecture and Design: Data design, Architectural Design Process, SADT, OOAD, function-oriented
design

UML: Use case diagram, State diagram, Activity Diagram, Class Diagram, Sequence diagram,
Collaboration diagram, Deployment Diagram, Event trace diagram, Design Patterns: Structural Patterns,
Behavioral Patterns, Creational Patterns

Software Estimation- Estimating Size, Effort and Cost: Metric for Analysis, Metric for Design, COCOMO
model, Putnam Model etc., Implementation and Integration: Coding standard and practices, Top-Down
and Bottom–up Approach, Verification and Validation,

Software Testing: Structural testing, functional Testing, Testing Strategies, Test Case design.

Software Maintenance: Types, Cost of Software, maintenance, Software Maintenance Models

CASE Tool Taxonomy: Business Process Engineering tool, Process modeling and management tool,
project planning tool, requirement tracking tool, Metric and management tool, documentation tool, system
software tool etc. Introduction to software engineering for web and mobile applications.
Teaching Methodology:
This course should be conducted in a highly interactive environment. Students will work on different
software projects in small groups. Exercises shall almost exclusively consist of design work and the
laboratory shall be a place to develop these designs using CASE tools. As part of lab work there shall be a
project to build a specification and convert it into working software using Rational Unified Process. Also,
there shall be a testing project. There is a self learning component that shall be announced.

Evaluation Scheme:
Exams Marks Coverage
Test-1 15 Marks Based on Unit-1 & Unit-2
Based on Unit-3 to Unit-4 and around 20% from
Test-2 25 Marks
coverage of Test-1
Based on Unit-5 to Unit-6 and around 40% from
Test-3 35 Marks
coverage of Test-2
Assignment 10 Marks
Tutorials 5 Marks
Quiz 5 Marks
Attendance 5 Marks
Total 100 Marks

Text Book

1. The Unified Modeling Language Users Guide: Grady Booch, James Rambaugh, Ivar Jacobson,
Addision Wesley.
2. Douglas Bell, “Software Engineering for students: a programming approach”, 4th Ed Pearson
Education, 2005.
3. Dines, Bjorna “Software Engineering: abstraction and Modelling”Vol.1, 2006, Springer
Verlag Berlin Heidelberg (206).
4. Cooling Jin, “Software Engineering for real time systems, Addison Wesley.
5. Khoshgoftaar, Taghi M. “Software Engineering with Computational Intelligence”.
6. Sommerville, Ian, “Software Engineering”, 8th Edition, Pearson Education Ltd.
7. Pressman S. Roger, “Software Engineering: A practitioner's Approach”, 7th Edition, McGraw
Hill.

Web References:
1. https://onlinecourses.nptel.ac.in/noc20_cs68/preview
2. https://online.visual-paradigm.com/
3. https://www.coursera.org/learn/introduction-to-software-engineering
Title of Course: Algorithms and Problem Solving Course Code: CS106
L-T Scheme: 3-1-0 Course Credit: 4

Prerequisites:
Student must have already registered for “Introduction to Computer and programming” (07B11CI101),
Data Structures (07B21CI102).

Objectives:
● Strengthen higher level cognitive Skills of analysis, creation and evaluation.
● Strengthen Ability of data abstraction and problem solving using computer
● Strengthen ability to express solution to problem clearly and precisely.
● Strengthen ability to design and evaluate ADTs, nonlinear temporary and persistent data
structures and also related algorithms.
● Introduce students to some domain specific data structures and related algorithms in various
domains.

Learning Outcomes:

Upon completion of the subject, students will be able to:

1 Get familiar with different basic concepts of algorithms and analyze the performance of
algorithms.
2 Have a good grounding of advance data structures like R-B Tree, M – way tree, models
and IDEs.
3 Get to learn about various algorithm design techniques for developing algorithms.

4 Possess demonstrative skills in solving optimization problems.

5 Be able to design, develop algorithms, and employ appropriate data structures for
solving real world computing problems efficiently.

Course Content:
Analysis of algorithm: Asymptotic Notation, Sorting and merging Algorithm
Tree and related data Structure: Heap, Priority Queues, B+ Tree, AVL, Splay Tree, Red-Black Tree,
Threaded Tree
Files: Classification, Record Organization, Retrieval System, External Sorting
Set, Dictionary: Design, Analysis, integration and applications
Fundamental techniques: Divide and Conquer method, Dynamic Programming, Introduction to Greedy
Method
Hashing: technique, collision resolution and analysis
Text Processing: String operation, pattern matching algorithm, tries, text compression, text similarity
testing.

Teaching Methodology:

The Course will use the mixed technique of interactive lectures, guided case studies, literature survey,
regular assignments and project work. In addition to the material covered in the class, student will be
required to explore study, evaluate present and implement domain specific data structure in different
domain. Teaching in this course is designed to engage the student in active and experimental learning by
taking a problem solving and design oriented approach with special emphasis on real world applications.
Lectures will be highly interactive and work oriented. Student will have to work individually as well as in
groups inside as well as outside the class. Students are expected to carry out a lot of design and
programming oriented project work. Each student is expected to write minimum 3000 lines of
documented program code as part of this course. Students are encouraged to learned use toolkits like STL
for project implementation. Each student is also expected to do literature survey making use of the library
and web resources (including digital library) to identify ,understand ,summarize and present at least one
research paper on science and application of non-linear data structure and algorithms.

Evaluation Scheme (Theory):

Evaluation Scheme is designed to promote and test higher level thinking skills and de-emphasis rote
learning through holistic and continuous evaluation. Written exam will be designed and conducted as open
Book(s), open notes tests. One of the minor tests may me designed and conducted as a take home test.
Evaluation scheme will have following components

Test-1 15 Marks
Test-2 25 Marks
Test-3 35 Marks
Home assignment /Quizzes 10 Marks
Tutorial/Problem solving session 10 Marks
Attendance 05 Marks
Total 100 Marks

Text book
T1: Thomas H., Coremen: Introduction to algorithm, the Massachusetts institute of Technology,
Cambridge, Massachusetts.

Reference Books:
1. Aho, Hopcraft, Ullman: Data Structure and Algorithms
2. Kruse, Tonso, Leung: Data Structure and program Design in C
3. Sahni: Data structure and algorithm and application in C++
4. Weiss: Data Structure and Algorithm analysis in C/C++
Course Name: Digital Systems and Computer Organization Code: CSXXX
L-T-P scheme: 3-0-0 Credits: 3

Learning Outcomes:

Course Description
Outcome
CO1 Develop the understanding of data representation and digital logic circuits used in the
computer system.
CO2 Concepts of Register Transfer Language (RTL) to design data transfer bus,
combinational and sequential logic circuits.
CO3 Understand the programming of basic computer system using machine language,
assembly language and microinstructions.
CO4 Describe the various architectures of CPU and their designing concepts.
CO5 Memory hierarchy, cache memory, virtual memory and their working
principle/performance.

Course Contents:

Unit I:
Review of number systems, Binary arithmetic, BCD code, Excess-3 code and Gray Codes. and
Boolean algebra, Standard and canonical representation and minimization of Boolean expressions
using Karnaugh Map and Quine–McClausky methods, Data Representation Types,
Complements, Fixed Point Representations, Floating Point Representations.

Unit II:
Combinational Circuits: Logic gates, Half & full adder and subtractor, Parallel adder, BCD
adders, Lookahead carry generator. Decoders, Encoders, Multiplexers and De-multiplexers, Code
convertor, Comparator, Parity generator and Checker. Seven Segment Display, Binary multiplier.
Sequential Circuits: Flip Flops, Registers, Counters.

Unit III:
Register Transfer and Micro operations: Register Transfer Language, Register Transfer, Bus
and Memory Transfers, Arithmetic Micro operations, Logic Micro operations, Shift Micro
operations, Arithmetic Logic Shift Unit. Basic Computer Organization and Design-Instruction
Codes, Computer Registers, Computer Instructions, Design Of Basic Computer, Design Of
Accumulator Logic, Basic Computer Programming in Assembly Language.

Unit IV:
Central Processing Unit: Introduction To CPU, General Register Organization, Stack
Instruction Formats, Addressing Modes, Data Transfer and Manipulation, Program Control,
Reduced Instruction Set Computer. Pipelining and Vector Processing - Parallel Processing,
Pipelining, Arithmetic Pipeline, Instruction Pipeline, RISC Pipeline, Multiprocessors-
Characteristics of Multiprocessors. Introduction to Computer Arithmetic, Addition and
Subtraction, Multiplication algorithms, Division algorithms, floating point arithmetic Operations.
Unit V:
Classification of Memory, Memory Organization, Memory Hierarchy, Main Memory, Auxiliary
Memory, Associative Memory, Cache Memory, Virtual Memory, Memory Management
Hardware. Page Replacement Algorithms,

Evaluation Scheme:
Exams Marks Coverage
Test-1 15 Marks Based on Unit-1 & Unit-2
Based on Unit-3 & Unit-4 and around 20-30%
Test-2 25 Marks
from coverage till Test-1
Based on Unit-5 to Unit-6 and around 30% from
Test-3 35 Marks
coverage till Test-2
Assignment 10 Marks
Tutorials 5 Marks
Quiz 5 Marks
Attendance 5 Marks
Total 100 Marks

Text Books

1. “Digital Logic and Computer Design”, M. Morris Mano, PHI.

2. “Computer System Architecture”, M. Morris Mano, Third Edition.
3. “Computer Organization and Architecture”, William Stalling, Tenth Edition.

Other References:

Resources
Lecture presentations, assignments and practicals, will be posted on the student resource from
time to time. In addition following additional online/downloadable resources will be useful.
● NPTEL Course: Computer architecture and organization, IIT Kharagpur by Prof. Indranil
Sengupta, Prof. Kamalika Datta, https://nptel.ac.in/courses/106105163
● Official IA-32 Programmer Reference Manuals online at
http://developer.intel.com/design/Pentium4/documentation.htm
● Professor Ralf Brown's Interrupt List online at http://www.ctyme.com/rbrown.htm
● Homepage for H. Peter Anvin's SYSLINUX Project online at http://syslinux.zytor.com/
● Online article: The GNU GRUB Boot Loader by Jaswinder Singh Kohli (Linux Gazette
#64, 2001)
Title of Course: Machine Learning Course Code: CS108
L-T-P scheme: 3-0-0 Credit: 3

Prerequisite: The mathematical tools needed for the course will be covered in some classes in
the first week of the course.

Objective:
1. To learn and be able to implement the basic statistical techniques in the areas of interest.
2. To develop the abilities to apply the basic Machine Learning algorithms and interpret their
results.

Learning Outcomes:

At the end of the course, students:

1. Get familiar with the fundamental methods at the core of modern machine learning.
2. Have a good grounding of the essential algorithms for supervised and unsupervised learning
3. Possess demonstrative skills in using and applying Machine Learning.
4. Work as a team on a project.

Course
Description
Outcome
CO1 List various approaches of Machine Learning.
CO2 Describe machine learning algorithms to solve the real world problems
CO3 Develop Hypothesis and machine learning models
CO4 Identify appropriate models for solving machine learning problems.
CO5 Apply learning techniques to solve real world machine learning problems
CO6 Evaluate and interpret the results of the algorithms.

Course Content:

Unit-I: Introduction to machine learning, supervised and unsupervised machine learning,

Applications of AI and machine learning , Linear Algebra, Matrices, Multi-Variable Calculus and
Vectors, Mean, Median, mode, Dispersion.

Unit-II: Probability, Probability Distributions, and Central Limit Theorem.

Hypothesis Testing: The what, why and how of Hypothesis Testing are covered in this module.
P-Value, different types of tests and implementation in Python.
Exploratory Data Analysis: EDA brings out the information from the Data. This module covers
Data Cleaning, Univariate/ Bivariate analysis.

Unit-III: Linear Regression: Simple and Multiple, Issues in Regression like Collinearity. Project
on Linear Regression. Logistic Regression Univariate and Multivariate Logistic Regression for
classification in ML, Implementation in R/Python, Naive Bayes Classification. Bias-Variance
Tradeoff, Evaluation metrics: Confusion Matrix, F1 Score, Root Mean Squared Error.

Unit-IV: Decision Tree, Random Forest, SVM, Validation Techniques: Leave one out cross-
validation, K-fold cross-validation, Stratified k-fold cross-validation.

Unit-V: K-Means clustering, Introduction to Neural Networks, Convolutional Neural Network.

Teaching Methodology:
This course is introduced to help students understand the discipline of Machine Learning. The
programming tool used to teach this course are R and Python. Starting from the basic
mathematical tools, the student will slowly be exposed to inferential statistics, and later to
Machine Learning Algorithms. This theory course is well complemented by a laboratory course
under the name Machine Learning Lab in the same semester that helps a student learn with hand-
on experience.

Evaluation Scheme:
Exams Marks Coverage
Test-1 15 Marks Based on Unit-1 & Unit-2
Based on Unit-3 & Unit-4 and around 20-30%
Test-2 25 Marks
from coverage till Test-1
Based on Unit-5 to Unit-6 and around 30% from
Test-3 35 Marks
coverage till Test-2
Assignment 10 Marks
Tutorials 5 Marks
Quiz 5 Marks
Attendance 5 Marks
Total 100 Marks

Learning Resources:
Tutorials and lecture slides on Machine Learning (will be added from time to time):
Digital copy will be available on the JUET server.
Text Book:
● Hastie, Tibshirani and Friedman. Elements of statistical learning.
Reference Material:
● L. Rosasco. Introductory Machine Learning Notes.
● Larry Wasserman. Clustering chapter
 Title: Algorithms Lab Code: CS207
L-T-P scheme: 0-0-2 Credit: 1

Prerequisite: Experience in programming is desirable. Student must have already registered for
“Software Development Lab” (18B17CI171) and “Data Structures lab” (18B17CI371).

Objective:

1. To provide exposure to problem-solving through programming.

2. Strengthen higher level cognitive Skills of analysis of problem, creation of solution and
evaluation of performance.
3. Strengthen Ability of data abstraction and problem solving using computer
4. Strengthen ability to express solution to problem clearly and precisely.
5. Strengthen ability to design and evaluate ADTs, nonlinear temporary and persistent data
structures and also related algorithms.
6. Introduce students to some domain specific data structures and related algorithms in
various domains.

Learning Outcomes:
Course Description
Outcome
CO1 Design new algorithms, prove them correct, and analyze their asymptotic and
absolute runtime and memory demands.
CO2 Find an algorithm to solve the problem (create) and prove that the algorithm
solves the problem correctly (validate).
CO3 Understand the mathematical criterion for deciding whether an algorithm is
efficient, and know many practically important problems that do not admit any
efficient algorithms.
CO4
Apply classical sorting, searching, optimization and graph algorithms.
CO5 Understand basic techniques for designing algorithms, including the techniques
of Recursion, Divide-and-Conquer, Greedy Algorithms and Dynamic
Programming

Course Content:
The following assignments will be carried out in synchronization with the theory classes.

Unit-1: Development of programs including analysis of algorithm Asymptotic Notation, Sorting and
merging Algorithm.

Unit-II: Programs using Heap, Priority Queues, B-Tree, AVL, Splay Tree, Red-Black Tree, Threaded
Tree.
Unit-III: Programs using Classification, Record Organization, and Retrieval System of files External
Sorting. Design, Analysis, integration of set & dictionary, collision resolution and analysis
Unit-IV: Programs using Divide and Conquer method, Dynamic programming, Introduction to
Greedy Method.

Unit-V: Program using String operation, pattern matching algorithm, tries, text compression, text
similarity testing application.

Units to Lab Mapping:

Unit Labs
I 1, 2, 3
II 4, 5
III 6, 7, 8
IV 9, 10, 11
V 12, 13, 14

Teaching Methodology:

This course is introduced to help students understand the designing and analysis of algorithm.
Any ( C, C++, JAV etc) programming language used to implement algorithms. Starting from the
programming environment setup, the student will slowly be exposed to program designing and
later to complexity analysis fundamentals. The entire course is broken down into five separate
units, from fundamentals of algorithms to some complex algorithms designing methodology like
Dynamic Programming Greedy Techniques etc.

Evaluation Scheme:

Exams Marks Coverage

P-1 15 Marks Based on Lab Exercises: 1-6
P-2 15 Marks Based on Lab Exercises: 7-13
Viva 20 Marks
Demonstration 20 Marks
Day-to-Day Work 70 Marks
Lab Record 15 Marks
Attendance & Discipline 15 Marks
Total 100 Marks

Learning Resources:

Study material of Algorithms Lab (will be added time to time): Digital copy will be
available on the JUET server.

Text Book:
1. Thomas H., Coremen: Introduction to algorithm, the Massachusetts institute of
Technology, Cambridge, Massachusetts.
Reference Books/Material:

1. Aho, Hopcraft, Ullman: Data Structure and Algorithms

2. Kruse, Tonso, Leung: Data Structure and program Design in C
3. Sahani: Data structure and algorithm and application in C++
4. Weiss: Data Structure and Algorithm analysis in C/C++

Online Courses:
NPTEL-Algorithms and Problem Solving: https://nptel.ac.in/courses/106/105/106105164/

Videos Available on YouTube:

https://www.youtube.com/watch?v=OQ5jsbhAv_M

https://www.youtube.com/watch?v=huQojf2tevI
https://www.youtube.com/watch?v=sSno9rV8Rhg

Website

● https://www.geeksforgeeks.org
● https://www.indiabix.com
● https://www.includehelp.com
● https://www.tutorialspoint.com
● https://www.sanfoundry.com
● https://www.programiz.com

Coding Platforms

● https://www.codechef.com
● https://www.hackerrank.com
● https://www.interviewbit.com
● https://www.spoj.com
● https://www.hackerearth.com
● https://leetcode.com

Integrated Development Environment

● Turbo C++
● Dev-c++
● Code::Block
Title of Course: Digital Systems and Computer Organization Lab Course Code: CSXXX
L-T-P scheme: 0-0-2 Credit: 1

Objective:
1. To design and verify digital circuits and basic computer system using LogiSim
simulator.
2. To acquire the hardware development skill through various stages of designing.

Learning Outcomes:

Course Outcome Description

CO1 Implementation of combinational logic circuits.
CO2 Designing of basic building blocks of a computer system.
CO3 Learn to design the ALU of a computer system.
CO5 Designing of sequential logic circuits for a computer system
CO5 Memory (RAM/ROM) system designing.

Course Content:

Unit-1; Introduction to LogiSim simulator.

Unit-2: Design of basic digital circuits using logic gates.
Unit-3: Design of binary adders and subtractors.
Unit-4: Design of combinational logic circuits.
Unit-5: Design of logic circuits using mux, encoder and seven segment displays.
Unit-6: Design of common bus, logic unit and shift unit.
Unit-7: Design of Arithmetic Logic Shift Unit and Multiplier.
Unit-8: Design of sequential circuits and digital clock.
Unit-9: Design of accumulator and basic CPU.
Unit-10: Design of ROM and RAM.

Evaluation Scheme:

Exams Marks Coverage

P-1 15 Marks Based on Lab Exercises: 1-5
P-2 15 Marks Based on Lab Exercises: 6-10
Viva 20 Marks
Demonstration 20 Marks
Day-to-Day Work Lab Record 15 Marks 70 Marks
Attendance & Discipline 15 Marks
Total 100 Marks
Learning Resources:

Soft copies of study material and lab exercises of Digital Systems and Computer Organization
Lab are made available on the JUET server.

Text Book
1. “Computer System Architecture” by M Morris Mano, Third Edition.

Other References:

1. Computer System Organization and Architecture: Designing for Performance” by W

Stallings, Seventh Edition, Prentice Hall, 2006. ISBN: 0-13-185644-8.

Resources

Lecture presentations, assignments and practicals, will be posted on the student resource from
time to time. In addition following additional online/downloadable resources will be useful.
• NPTEL Course: Computer architecture and organization, IIT Kharagpur by Prof. Indranil
Sengupta, Prof. Kamalika Datta, https://nptel.ac.in/courses/106105163
• Virtual Lab: http://vlabs.iitkgp.ac.in/coa
Title of Course: Machine Learning Lab Course Code: CS209
L-T-P scheme: 0-0-2 Credit: 1

Prerequisite: The mathematical tools needed for the course will be covered in some classes in
the first week of the course.

Objective:
1. To learn and be able to implement the basic statistical techniques in the areas of interests.
2. To develop the abilities to apply the basic Machine Learning algorithms and interpret their
results.

Learning Outcomes:
At the end of the course, students:

Course
Description
Outcome
Get familiar with the fundamental methods at the core of modern machine
CO1
learning.
Have a good grounding of the essential algorithms for supervised and
CO2
unsupervised learning
CO3 Possess demonstrative skills in using and applying Machine Learning.
CO4 Work as a team on a project.

Course Content:
Unit-I: Introduction to machine learning, supervised and unsupervised machine learning,
Applications of AI and machine learning , Linear Algebra, Matrices, Multi-Variable Calculus and
Vectors, Mean, Median, mode, Dispersion.

Unit-II: Probability, Probability Distributions, and Central Limit Theorem.

Hypothesis Testing: The what, why and how of Hypothesis Testing are covered in this module.
P-Value, different types of tests and implementation in Python.
Exploratory Data Analysis: EDA brings out the information from the Data. This module covers
Data Cleaning, Univariate/ Bivariate analysis.

Unit-III: Linear Regression: Simple and Multiple, Issues in Regression like Collinearity. Project
on Linear Regression. Logistic Regression Univariate and Multivariate Logistic Regression for
classification in ML, Implementation in R/Python, Naive Bayes Classification. Bias-Variance
Tradeoff, Evaluation metrics: Confusion Matrix, F1 Score, Root Mean Squared Error.

Unit-IV: Decision Tree, Random Forest, SVM, Validation Techniques: Leave one out cross-
validation, K-fold cross-validation, Stratified k-fold cross-validation.

Unit-V: K-Means clustering, Introduction to Neural Networks, Convolutional Neural Network.

Teaching Methodology:
This course is introduced to help students understand the discipline of Machine Learning. The
programming tool used to teach this course are R and Python. Starting from the basic
mathematical tools, the student will slowly be exposed to inferential statistics, and later to
Machine Learning Algorithms. This theory course is well complemented by a laboratory course
under the name Machine Learning Lab in the same semester that helps a student learn with hand-
on experience.

Evaluation Scheme:

Evaluations Marks Remarks

P-1 15 Marks
P-2 15 Marks
Viva 20 Marks
Demonstration 20 Marks
Continuous
Lab Record 15 Marks
Evaluations
Discipline and
Punctuality and 15 Marks
Attendance
Total 100 Marks

Learning Resources:

Lab exercises and lecture slides on Machine Learning (will be added from time to time):
Digital copy will be available on the JUET server.

Text Book:
● Hastie, Tibshirani and Friedman. Elements of statistical learning.

Reference Material:
● L. Rosasco. Introductory Machine Learning Notes.
● Larry Wasserman. Clustering chapter
Title of Course: Mobile and Application Development Lab Course Code: CS210

L-T-P scheme: 0-0-2 Credit: 1

Prerequisite: Students must have already registered for the course, “Introduction to Computers
and Programming” and “Object Oriented Programming”.

Objective:

1. To learn and be able to implement different mobile-technologies.

2. To develop the abilities to call oneself mobile application developer.

Learning Outcomes:
At the end of the course, a student will:
1. Get familiar with different approaches to mobile application development.
1. Get to learn about application marketing.
2. Have a good grounding of mobile application development requirements, models and
IDEs.
3. Possess demonstrative skills in building native applications.
4. Be able to design and develop cross-platform applications.
5. Learn to work in a team on a project.

Course Content:
Part-1: Orientation and Fundamentals of Development
Unit-1 Mobile applications and different approaches to mobile application development. Java
features and review of Object Oriented Programming fundamentals.
Part-2: Android Studio and Basic Development Skills
Unit-2 Installing and getting accustomed to the android studio environment. Using activities and
views. Working on different views like TextViews, ImageViews etc. Creating simple
applications using basic view types.
Unit-3 Using animations, audio and video. Advanced android features like list views, Exception
handling, Timers in androids, Advanced String manipulations.
Part-3: Serious Development
Unit-4 Maps and GeoLocation, Storing data permanently, Alert dialogs, SQLite databases,
Advanced SQLite, Webviews.
Unit-5 Submitting app to distribution channels, marketing mobile app, Mobile App development
models.
Part-4: Working in a team and Cross Platform Development
Unit-6 Using Git, Common Git commands, Project Development, Cross Platform Development
using Flutter, Coding using Dart, MVC design pattern, Networking, Data storage, Authentication,
State Management.

Teaching Methodology:
This course is introduced to help students transition from a regular developer to a mobile app
developer. Starting from the basics, the student will slowly progress to become to other aspects of
development including database, version control and other essential technologies that are helpful
for a developer. The entire course is broken down into four separate parts: Orientation and
Fundamentals of Development, Android Studio and Basic Development Skills, Serious
Development, and Working in a team and Cross Platform Development. Each section includes
multiple technologies to help a student gain more experience as a developer. This lab course is
well complemented by a lecture in the same semester that helps a student learn and discuss the
technical details of the underlying technologies.

Evaluation Scheme:
Exams Marks Coverage
P-1 15 Marks Based on Lab Exercises: 1-7
P-2 15 Marks Based on Lab Exercises: 8-14
Viva 20 Marks
Demonstration 20 Marks
Day-to-Day Work 70 Marks
Lab Record 15 Marks
Attendance & Discipline 15 Marks
Total 100 Marks

Learning Resources:
Tutorials and lecture slides on Mobile Development (will be added from time to time): Digital
copy will be available on the JUET server.

Books: Text Book

1. Hello, Android (3rd edition): Introducing Google's Mobile Development Platform by Ed
Burnette ISBN: 978-1-93435-656-2
2. Android Programming for Beginners: Build in-depth, full-featured Android 9 Pie apps
starting from zero programming experience, 2nd Edition by John Horton ISBN: 978-
1789538502
3. Head First Android Development: A Brain-Friendly Guide 1st Edition by Dawn
Griffiths, David Griffiths. ISBN: 978-1449362188

Reference Books
1. Android Programming: The Big Nerd Ranch Guide (3rd Edition) (Big Nerd Ranch
Guides) 3rd Edition by Bill Phillips, Chris Stewart, Kristin Marsicano ISBN: 978-
0134706054
2. The Busy Coder's Guide to Android Development Version 8.0 by Mark M Murphy (O nline
Book)

Web References:
1. https://developer.android.com
2. https://www.androidauthority.com
3. https://www.vogella.com

Journals:
1. International Journal of Interactive Mobile Technologies (iJIM)
2. ACM Transactions on the Information Systems (TOIC).
3. International Journal of Modern Computer Science (IJMCS)
4. ACM Transactions on Internet Technology (TOIT).