COURSE FILE

ON

AD3301

DATA EXPLORATION AND VISUALIZATION

II B.TECH AI&DS
III-SEMESTER
2024-2025

Prepared by

Mrs.M.BHUVANESWARI M.E.,

Assistant Professor
 DEPARTMENT OF ARTIFICIAL INTELLIGENCE &DATA SCIENCE

Academic Year 2024-2025

Course Title DATA EXPLORATION AND VISUALIZATION
Course Code AD3301
Programme B.TECH
Year & Semester IIyear III-semester
Branch & Section AI&DS
Regulation R21
Course Faculty Mrs.M.BHUVANESWARI M.E.,AP/AI&DS

Index of Course File

S. No. Name of the content

1 Institute vision and mission
2 Department vision and mission /PEO
3 POs /PSOs
4 Course Syllabus with Structure
5 Course Outcomes (CO)
6 Mapping CO with PO/PSO; Course with PO/PSO with Justification
7 Academic Calendar
8 Time table - highlighting your course periods including tutorial
Lesson plan with number of hours/periods, TA/TM, Text/Reference
9
Book
10 Web references
11 Lecture notes
12 List of Power point presentations / Videos
13 University Question papers
14 Internal Question papers, Key with CO and BT
15 Assignment Question papers mapped with CO and BT
Result Analysis to identify weak and advanced learners - 3 times in a
16 Semester
17 Result Analysis at the end of the course
18 Advance Learners- Engagement documentation
19 CO, PO/PSO attainment sheets
Attendance register (Theory/Tutorial/Remedial) - Teacher/Course
20
delivery record; Continuous evaluation
21 Course file (Digital form)
 DEPARTMENT OF ARTIFICIAL INTELLIGENCE &DATA SCIENCE

INSTITUTE VISION AND MISSION

Vision:
To function as a center of excellence with world-class instructional and
infrastructural facilities to realize the vision of producing highly disciplined,
talented students to serve humanity in unparalleled style.

Mission:
To produce graduates worthy of appropriate to a professional person,
competent, skillful or assured to render service of global standards.
 DEPARTMENT OF ARTIFICIAL INTELLIGENCE &DATA SCIENCE

DEPARTMENT VISION AND MISSION

Vision:
A field of computer science that trains computers to replicate the human vision
system. This enables digital devices (like face detectors, QR Code Scanners) to
identify and process objects in images and videos, just like humans do.

Mission:
The primary objectives of the AI Mission includes establishing robust computing
powers for AI within India. The mission seeks to enhance services for startups and
entrepreneurs while fostering AI applications in critical sectors such as agriculture,
healthcare, and education.
 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

PROGRAM EDUCATIONAL OBJECTIVES

PEO1: Implement computing solutions for real world problems and carry out basic
and applied research leading to new innovations in Information Technology
(IT) and related interdisciplinary areas.

PEO2: Apply knowledge of societal impacts of information technologies in the course

of their career related activities ethically and appropriately.

PEO3: Have strong communication and interpersonal skills, broad knowledge, and
an understanding of multicultural and global perspectives to work effectively
and ethically in multidisciplinary teams, both as team members and leaders.

PEO4: Engage in life-long learning, to remain current in their profession and obtain
additional qualifications to enhance their career positions in IT industries.

PROGRAM SPECIFIC OUTCOMES

PSO1 : Professional Skills: To implement computer programs of varying complexity

in the areas related to Web Design, Cloud Computing, Network Security and
Artificial Intelligence.

PSO2: Problem-Solving Skills: To develop quality products using open ended

programming environment.
 PROGRAMME OUTCOMES (POs)

POS1: Engineering knowledge: Apply the knowledge of mathematics, science,

engineering, data science fundamentals, and artificial intelligence to solve complex
engineering problems.
POS2: Problem analysis: Identify, formulate, review research literature and analyze
complex engineering problems to create solutions using the first principles of
mathematics, engineering sciences, and data science.
POS3: Design/development of solutions: Design solutions for complex
engineering problems and design system components or processes that meet the
specified needs with appropriate consideration for the public health and safety, and
the cultural, societal, and environmental considerations.
PSO4 : Conduct investigations of complex problems: Apply research methods including
design of experiments, statistical analysis and business interpretation of data, and
synthesis of the information to provide valid conclusions.
PSO5: Modern tool usage: Create, select, and apply appropriate Artificial intelligence
principles, techniques, modern engineering and IT tools including prediction and
modelling to model complex engineering activities with an understanding of the
limitations.
PSO6: The engineer and society: Apply reasoning using contextual knowledge to assess
the needs of societal, health, safety, legal and cultural issues and the consequent
responsibilities relevant to data science engineering practice.
PSO7: Environment and sustainability: Understand the impact of artificial intelligence
solutions in societal and environmental contexts, and demonstrate the knowledge
for sustainable development.
PSO8: Ethics: Apply ethical principles and commit to professional ethics and to execute
responsibilities and adhere to norms of the engineering profession.
PSO9: Individual and team work: Execute professional functions effectively as an
individual, as well as a leader or member in diverse multidisciplinary teams.
PSO10: Communication: Communicate effectively with the engineering community and
with society in solving complex problems in terms of being able to comprehend and
write effective reports, make effective presentations, as well as execute and receive
clear instructions.
PSO11: Project management and finance: Demonstrate an ability to use management
principles and apply these to one’s own work, as a member and lead projects and
build cost models in an interdisciplinary professional setting.
PSO12: Lifelong learning:Inculcate the ability to prepare for lifelong learning in the context
of technological change.
 COURSE SYLLABUS WITH STRUCTURE
SEMESTER III
PERIODS TOTAL
S. COURSE CATE PER WEEK
COURSE TITLE CONTACT CREDITS
NO. CODE GORY
L T P PERIODS
THEORY
1. MA3354 Discrete Mathematics BSC 3 1 0 4 4
2. Digital Principles and
CS3351 PCC 3 0 2 5 4
Computer Organization
3. Database Design and
AD3391 PCC 3 0 0 3 3
Management
4. Design and Analysis of
AD3351 PCC 3 0 2 5 4
Algorithms
5. Data Exploration and
AD3301 PCC 3 0 2 5 4
Visualization
6. AL3391 Artificial Intelligence PCC 3 0 0 3 3
PRACTICALS
7. Database Design and 0 0 3 3
AD3381 PCC 1.5
Management Laboratory
8. Artificial Intelligence 0 0 3 3
AD3311 PCC 1.5
Laboratory
9. GE3361 Professional Development$ EEC 0 0 2 2 1
TOTAL 18 1 14 33 26

SEMESTER IV
PERIODS TOTAL
S. COURSE CATE PER WEEK
COURSE TITLE CONTACT CREDITS
NO. CODE GORY
L T P PERIODS
THEORY
1. MA3391 Probability and Statistics BSC 3 1 0 4 4
2. AL3452 Operating Systems PCC 3 0 2 5 4
3. AL3451 Machine Learning PCC 3 0 0 3 3
4. Fundamentals of Data Science PCC 3
AD3491 3 0 0 3
and Analytics
5. CS3591 Computer Networks PCC 3 0 2 5 4
6. Environmental Sciences and
GE3451 BSC 2 0 0 2 2
Sustainability
7. NCC Credit Course Level 2# 3 0 0 3 3#
PRACTICALS
8. Data Science and Analytics 0 0 4 4
AD3411 PCC 2
Laboratory
9. AD3461 Machine Learning Laboratory PCC 0 0 4 4 2
TOTAL 17 1 12 30 24
AD3301 DATA EXPLORATION AND VISUALIZATION L T P C
3 0 2 4
OBJECTIVES:
• To outline an overview of exploratory data analysis.
• To implement data visualization using Matplotlib.
• To perform univariate data exploration and analysis.
• To apply bivariate data exploration and analysis.
• To use Data exploration and visualization techniques for multivariate and time series data.

UNIT I EXPLORATORY DATA ANALYSIS 9

EDA fundamentals – Understanding data science – Significance of EDA – Making sense of data –
Comparing EDA with classical and Bayesian analysis – Software tools for EDA - Visual Aids for EDA-
Data transformation techniques-merging database, reshaping and pivoting, Transformation
techniques - Grouping Datasets - data aggregation – Pivot tables and cross-tabulations.

UNIT II VISUALIZING USING MATPLOTLIB 9

Importing Matplotlib – Simple line plots – Simple scatter plots – visualizing errors – density and
contour plots – Histograms – legends – colors – subplots – text and annotation – customization – three
dimensional plotting - Geographic Data with Basemap - Visualization with Seaborn.

UNIT III UNIVARIATE ANALYSIS 9

Introduction to Single variable: Distributions and Variables - Numerical Summaries of Level and
Spread - Scaling and Standardizing – Inequality - Smoothing Time Series.

UNIT IV BIVARIATE ANALYSIS 9

Relationships between Two Variables - Percentage Tables - Analyzing Contingency Tables -
Handling Several Batches - Scatterplots and Resistant Lines – Transformations.

UNIT V MULTIVARIATE AND TIME SERIES ANALYSIS 9

Introducing a Third Variable - Causal Explanations - Three-Variable Contingency Tables and Beyond
- Longitudinal Data – Fundamentals of TSA – Characteristics of time series data – Data Cleaning –
Time-based indexing – Visualizing – Grouping – Resampling.

45 PERIODS
COURSE OUTCOMES:
At the end of this course, the students will be able to:
CO1: Understand the fundamentals of exploratory data analysis.
CO2: Implement the data visualization using Matplotlib.
CO3: Perform univariate data exploration and analysis.
CO4: Apply bivariate data exploration and analysis.
CO5: Use Data exploration and visualization techniques for multivariate and time series data.
TEXT BOOKS:
1. Suresh Kumar Mukhiya, Usman Ahmed, “Hands-On Exploratory Data Analysis with Python”, Packt
Publishing, 2020. (Unit 1)
2. Jake Vander Plas, "Python Data Science Handbook: Essential Tools for Working with Data", Oreilly,
1st Edition, 2016. (Unit 2)
3. Catherine Marsh, Jane Elliott, “Exploring Data: An Introduction to Data Analysis for Social
Scientists”, Wiley Publications, 2nd Edition, 2008. (Unit 3,4,5)

REFERENCES:
1. Eric Pimpler, Data Visualization and Exploration with R, GeoSpatial Training service, 2017.
2. Claus O. Wilke, “Fundamentals of Data Visualization”, O’reilly publications, 2019.
3. Matthew O. Ward, Georges Grinstein, Daniel Keim, “Interactive Data Visualization:
Foundations, Techniques, and Applications”, 2nd Edition, CRC press, 2015.

CO’s- PO’s & PSO’s MAPPING

PO’s PSO’s
CO’s 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3
1 3 1 3 3 - - - - 2 3 3 3 2 2 2
2 2 2 2 1 1 - - - 3 2 3 1 3 1 3
3 2 1 2 1 1 - - - 3 2 1 2 2 2 1
4 2 2 2 1 - - - - 1 2 1 3 1 3 2
5 3 1 1 2 1 - - - 3 2 1 2 2 2 3
AVG 2 1 2 2 1 - - - 2 2 2 2 2 2 2
1 - low, 2 - medium, 3 - high, ‘-' - no correlation
Mapping of course outcomes with program outcomes:
High -3 Medium -2 Low-1
PO/PSO/
PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2
CO
C305.1 3 2 2 2 - - - - - - - - 2
C305.2 3 2 2 2 - - - - - - - 2 1 2
C305.3 3 2 2 2 - - - - - - - - 2
C305.4 3 1 2 2 - - - - - - - - 1 2
C305.5 2 1 1 2 - - - - - - - - 2 1
C305.6 3 2 2 2 - - - - - - - - - 2
C305 2.8 1.6 1.8 2 - - - - - - - - 1.6 1.75
 CO-PO Mapping Justification
C305.1 Express syntax and semantics in formal notation. (Comprehension)

Justification
PO1 Knowledge of Engineering Fundamentals by using syntax and Semantics.
PO2 Identify and formulate the engineering problems by using basic notations & grammars.
PO3 Design solutions for complex problems by using different formal notations.
PO4 Define the complex problems course content and the need for formal notation.
PSO1 Importance of integrating professional skills within the context of syntax and semantics.

C305.2 Identify appropriate primitive /User defined data types for increasing program
efficiency.( Comprehension)

Justification
PO1 Improve the Knowledge by using various fundamentals.
PO2 Problem analysis is done by programming languages.
PO3 Design the solutions by using different programming languages.
PO4 Define the complex problems associated with program for increasing program efficiency.
PO12 Learning of data types which are used in developed programs.
PSO1 Emphasize the integration of professional skills within the context of data type selection.
PSO2 Explain the ability to choose appropriate data types directly contributes to the
development of these problem-solving skills

C305.3 Apply sub program concepts to improve the readability of the

program.(Application)

Justification
PO1 Knowledge is gained by using different types of data types.
PO2 Problem analysis applying sub program concepts.
PO3 Developing the solutions by taking programming concepts.
PO4 Complex problem to improve the readability of the program.
PSO1 Explain the use of subprograms directly contributes to the development of these
professional skills.
C305.4 Understand the concepts of ADT and OOP.(Knowledge)

Justification
PO1 Apply the knowledge of programming concepts.
PO2 Problem analysis understand the concepts of OOPs.
PO3 Development of solutions by using sub program concepts.
PO4 Complex problem are identified by using ADT.
PSO1 Explain a solid understanding of ADT and OOP contributes to the development of these
professional skills.
PSO2 Discuss real-world situations where understanding ADT and OOP facilitated effective
problem-solving and design solutions.

C305.5 Apply exception handling techniques to develop robust programs to sustain against all
runtime exceptions.(Application)

Justification
PO1 Apply the knowledge of exception handling techniques.
PO2 Analyze the concepts of runtime exceptions.
PO3 Develop the solutions by using Java Threads.
PO4 Define the complex problems associated with runtime exceptions that will be
investigated.
PSO1 Explain the proficiency in exception handling contributes to the development of these
professional skills
PSO2 Emphasize the integration of problem-solving skills within the context of exception
Handling

C305.6 Describe functional programming languages like LISP, ML, Haskell.(Knowledge)

Justification
PO1 Knowledge is gained by using logic and scripting programming.
PO2 Describe the functional programming languages are essential for problem analysis and
design solutions.
PO3 Design the solutions by using Functional Programming languages.
PO4 Discuss key features of functional languages that make them well-suited for solving
complex problems, such as immutability, higher-order functions, and strong type
systems.
PSO2 Discuss the knowledge of different programming paradigms, including functional
programming, expands problem-solving approaches.
 ACADEMIC CALENDAR (AY 2024-25 ODD Semester – III, V and VII) – PG
AUGUST Remarks
2024
SUN MO TUE WED THU FRI SAT 12th – Reopening Day
N 15th – Independence Day
1 2 3 26th – Gokulashtami
4 5 6 7 8 9 10
11 12 13 14 15 16 17
18 19 20 21 22 23 24
25 26 27 28 29 30 31
No. of working days : 13 Cumulative : 13

SEPTEMBER Remarks
2024
SUN MO TUE WE THU FRI SAT 7th – Vinayagar
N D Chathurthi 5th – Unit 1
1 2 3 4 5 6 7 Completion 16th – Miladi
Nabi
8 9 10 11 12 13 14
20th - Unit 2 Completion
15 16 17 18 19 20 21 23rd, 24th & 25th – Internal Exam I
22 23 24 25 26 27 28
29 30
No. of working days : 20 Cumulative : 33

OCTOBER Remarks
2024
SUN MO TUE WED THU FRI SAT 2nd – Gandhi Jayanthi
N 8th, 9th & 10th – Industrial Visit
1 2 3 4 5 11th & 12th – Saraswathi Pooja & Ayudha Pooja
6 7 8 9 10 11 12 15th – Unit 3
13 14 15 16 17 18 19 Completion 24 th – Unit
4 Completion
20 21 22 23 24 25 26 25th, 28th & 29th – Internal Exam II
27 28 29 30 31 31st – Deepavali Festival
No. of working days : 20 Cumulative : 53
NOVEMBER 2024 Remarks
SUN MO TUE WED THU FRI SAT 12th – Unit 5 Completion
N 13th, 14th,15th, 18th, 19th , 20th - Model Exam
1 2 21st & 22nd – Model Practical
3 4 5 6 7 8 9 22nd – Last working Day
10 11 12 13 14 15 16
17 18 19 20 21 22 23
24 25 26 27 28 29 30
No. of working days : 20 Cumulative : 73

HoD Principal
 LESSON PLAN
Course Title
Course Code
Programme B.Tech AI&DS
Year & Semester II-year III-semester
Regulation R21
Course Faculty Mrs.M.Bhuvaneswari M.E,AP/CSE

S.NO Unit TOPIC Number of Teaching REFERENCE

Sessions method/Aids
Planned
1 EDA fundamentals 1 Black Board T1

2 Understanding data science 1 Black Board T1

3 I – Significance of EDA 1 Black Board T1

4 Making sense of data 1 Black Board T1
5 Comparing EDA with classical and 1 Black Board T1
Bayesian analysis
6 Software tools for EDA 1 Black Board T1

7 Visual Aids for EDA- 1 Black Board T1

8 Data transformation techniques- 1 Black Board T1

9 merging database 1 Black Board T1

10 reshaping and pivoting 1 Black Board T1

11 Transformation techniques 1 Black Board T1

12 Grouping Datasets 1 Black Board T1

13 data aggregation 1 Black Board T1

14 Pivot tables and cross-tabulations. 1 Black Board T1

15
EB REFERENCE
S.No Web Link

1 https://www.youtube.com/watch?v=C_w9KU8P1gA&list=PLbWkMgLvWbDF3bErg6Ej
o8d1QtTSqtWwN
2 https://www.youtube.com/watch?v=iQzI2kwPXa0&list=PLbWkMgLvWbDF3bErg6Ejo
8d1QtTSqtWwN&index=2
3 https://www.youtube.com/watch?v=JOTknHd1S18&list=PLbWkMgLvWbDF3bErg6Ej
o8d1QtTSqtWwN&index=8
4 https://www.youtube.com/watch?v=c4WUzrk_Eq4&list=PLbWkMgLvWbDF3bErg6Ejo
8d1QtTSqtWwN&index=11
5 https://www.youtube.com/watch?v=KMNsqAQnTP4&list=PLbWkMgLvWbDF3bErg6
Ejo8d1QtTSqtWwN&index=15
 LECTURE NOTES

UNIT -1 Link:

https://drive.google.com/file/d/1apWdFPmV0M-Qqda0DwEp54hg0z2bArff/view?usp=sharing

UNIT-2 Link:
https://drive.google.com/file/d/13rJ1JqAznxvfQiXzhF5X80wIHynvaipb/view?usp=sharing

UNIT-3 Link:
https://drive.google.com/file/d/1xTHuPc-uybB3PV9-26jftclj08b2OpId/view?usp=sharing
UNIT-4 Link:
https://drive.google.com/file/d/1l6S_P0q7Eux9gJ9HmS5PUO4LiCF5k2a2/view?usp=sharing
UNIT-5 Link:
https://drive.google.com/file/d/1XX2g2mnK7t321FaSP8Uglr8wnTkfOYpa/view?usp=sharing

List of Power point presentations

Unit-1 Link :

https://docs.google.com/presentation/d/1RZQDiRc8q-rOGF1hm5eQ6GItWgIJ0-
S7/edit?usp=sharing&ouid=116740267257898588224&rtpof=true&sd=true

Unit-2 Link :
https://docs.google.com/presentation/d/1FWU1N1EZwV8ixGiYnQiBpCKjvL4HI7Ta/edit?usp=shar
ing&ouid=116740267257898588224&rtpof=true&sd=true
 Assignment Questions-I

(Assignment Questions are mapped with CO’s, BT)

1. Examine the three methods of implementing a programming language.(Comprehension)(C315.1)

2. Distinguish the significant characteristics of programming languages. (Synthesis) (C315.1)

3. Test for Union. What is the deference between record and Union ? Explain how Union is

supported by different programming languages. (Knowledge)(C315.2)

4. Inspect in detail counter controlled loops. (Comprehension)(C315.2)

5. Analyse the three semantic models of parameter passing. (Knowledge)(C315.3)

 Assignment Questions-II

(Assignment Questions are mapped with CO’s, BT)

1. Analyse parameterized abstract data types with an example in C++.

(Knowledge)( (C315.3)

2. Define Semaphores. Explain how Cooperation Synchronization & Competition

Synchronization are implemented using semaphores. (Knowledge)(C315.4)

3. Survey exception handling in Ada. (Comprehension)(C315.4)

4. Take part in simple functions in mathematical functions. (Knowledge)(C315.5)

5. Test for account on the history of Python language. (Comprehension)(C315.6)

Result Analysis:

Course Title DATA EXPLORATION AND VISUALIZATION

Course Code AD3301
Programme B.Tech AI&DS
Year & Semester II year IIISemester
Regulation R21
Course Faculty Mrs.M.Bhuvaneswari,M.E.,Assistant Professor , CSE

Advanced learners:

S No Roll no Internal-I Status Internal-II Status Model- Status

1 912523405001 78 70 83
2 912523405002 65 60 70
3 912523405003 68 65 65
4 912523405004 72 65 73
5 912523405005 70 68 74
6 912523405006 60 65 70
7 912523405007 80 75 78
8 912523405008 68 60 64
9 912523405009 55 50 58
10 912523405010 73 65 68
11 912523405011 74 68 72
Advanced learners:

S No Roll no GATE MATERIAL

1 Lexical analysis, parsing, syntax-directed translation Runtime environments
Intermediate code .Generation, Data propagation processes, threads, inter-process
2
communication, concurrency and synchronization. Deadlock CPU and I/O
3 management and virtual memory File systems.
4
5
6
7
8
9
10
11
 BATCH M.E CSE I-YR I SEM- A RESULT ANALYSIS

ACADAMIC COURSE NUMBER OF QUESTION PAPER

YEAR NAME STUDENTS SETTING PASS%
2023-24 Principles of APPEARED PASSED INTERNAL EXTERNAL
Programming COURSE
11 11 FACULTY EXTERNAL 100%
Languages

Principles of Programming Languages(C315) Result Analysis

70

60

50

40
APPEARED
30 PASSED

20

10

0
APPEARED PASSED
 Course Outcome Attainment (Internal Examination-1)
Name of the faculty :Mrs.S.Arulmozhi M.E.,AP/CSE Academic Year: 2023-24
Branch & Section :M. CSE Examination: I Internal

Course Name: PRINCIPLES OF PROGRAMMING Year: I Semester: I

LANGUAGES

S.No HT No. Q1 Q1b Q1c Q2a Q2b Q2C Q3A Q3b Q3c Q4a Q4b Q4c Obj1 A1
a
Max. Marks ==> 5 5 5 5 10 5
1 912523405001 2 2 9 5
2 912523405002 4 2 9 5
3 912523405003 3 8 5
4 912523405004 5 3 7 5
5 912523405005 4 2 7 5
6 912523405006 4 9 5
7 912523405007 2 5 9 5
8 912523405008 2 4 8 5
9 912523405009 1 2 8 5
10 912523405010 1 2 6 5
11 912523405011 4 4 7 5

Target set by the 2.0 0.00 0.00 2.00 0.00 0.00 2.00 0.00 0.00 2.00 0.00 0.00 4.00 2.00
faculty / HoD 0
Number of
students performed 15 0 0 0 0 0 42 0 0 60 0 0 63 63
above
Number of students
attempted 15 0 0 0 0 0 47 0 0 60 0 0 63 63

Percentage of students
scored more than 10 89% 100% 100% 100%
target 0%

CO Mapping with Exam Questions:

CO - 1 Y Y Y y y
CO - 2 Y Y y y
 CO - 3 Y y y
CO - 4
CO - 5
CO - 6

CO Attainment based on Exam Questions:

CO - 1 100% 100% 100%
CO - 2 89% 100% 100%
CO - 3 100% 100% 100%
CO - 4
CO - 5
CO - 6

CO Subj obj Asgn Overall Level Attainment Level

CO-1 100% 100% 100% 100% 3.00 1 40%
CO-2 89% 100% 100% 96% 3.00 2 50%
CO-3 100% 100% 100% 100% 3.00 3 60%
CO-4
CO-5
CO-6
Attainment (Internal 1 Examination) = 3.00
 Course Outcome Attainment (Internal Examination-2)

Name of the faculty : Mrs.S.Arulmozhi,AP/CSE Academic Year: 2023-24

Branch & Section : M.E CSE Examination: II Internal

Course Name : PRINCIPLES OF PROGRAMMING Year/Sem I/I

LANGUAGES

S.No Reg No. Q1 Q1b Q1c Q2a Q2b Q2c Q3a Q3b Q3c Q4a Q4b Q4c Obj4 A4
a
Max. Marks ==> 5 5 5 5 10 5
1 912523405001 2 2 7 5
2 912523405002 4 4 7 5
3 912523405003 4 7 5
4 912523405004 4 5 6 5
5 912523405005 3 5 7 5
6 912523405006 3 3 7 5
7 912523405007 3 5 7 5
8 912523405008 2 4 6 5
9 912523405009 3 4 7 5
10 912523405010 5 5
11 912523405011 5 3 7 5

Target set by the faculty / 2.00 0.00 0.00 2.00 0.00 0.00 2.00 0.00 0.00 2.00 0.00 0.00 4.00 2.00
HoD

Number of students 21 0 0 5 0 0 41 0 0 51 0 0 63 63
performed above the target

Number of students 22 0 0 5 0 0 41 0 0 51 0 0 63 63
attempted
Percentage of students
scored more than target 95 100% 100% 100% 100% 100%
%

CO Mapping with Exam Questions:

CO - 1
CO - 2
CO - 3
CO - 4 Y y y
CO - 5 Y y y
CO - 6 Y Y y y

% Students Scored
>Target % 95% 100% 100% 100% 100% 100%

CO Attainment based on Exam Questions:

CO - 1

CO - 2
CO - 3
CO - 4 95% 100% 100%
CO - 5 100% 100% 100%
CO - 6 100% 100% 100% 100%

CO Subj obj Asgn Overall Level Attainment Level

CO-1 1 40%
CO-2 2 50%
CO-3 3 60%
CO-4 95% 100% 100% 98% 3
CO-5 100% 100% 100% 100% 3
CO-6 100% 100% 100% 100% 3
Attainment (Internal Examination-2) = 3.00
 Course Outcome Attainment (University Examinations)
Name of the faculty : Mrs.S.Arulmozhi,AP/CSE Academic Year: 2023-24
Branch & Section: CSE- A Year / Semester: I/I
Course Name: PRINCIPLES OF PROGRAMMING LANGUAGES
S.No Roll Number Marks Secured
1 912523405001 78
2 912523405002 65
3 912523405003 68
4 912523405004 72
5 912523405005 70
6 912523405006 60
7 912523405007 80
8 912523405008 68
9 912523405009 55
10 912523405010 73
11 912523405011 74
Max Marks 75
Class Average mark 0
Number of students performed above the target 11 Attainment Level % students
Number of successful students 11 1 40%
2 50%
Percentage of students scored more than target 100% 3 60%
Attainment level 2
 Course Outcome Attainment

Name of the faculty : Mrs.S.Arulmozhi Academic Year: 2023-24

Branch & Section: CSE Examination: I Internal

Course Name: Principles Of Programming Languages Year: I

Semester: II
1st Internal 2nd Internal Internal
Course Outcomes Exam Exam Exam University Exam Attainment Level

CO1 3.00 3.00 2.00

2.25
CO2 3.00 3.00 2.00
2.25

CO3 3.00 3.00 2.00

2.25
CO4 3.00 3.00 2.00
2.25

CO5 3.00 3.00 2.00

2.25

CO6 3.00 3.00 2.00

2.25
Internal & University Attainment: 3.00 2.00

Weightage 25% 75%

CO Attainment for the course (Internal, University) 0.75 1.50

CO Attainment for the course (Direct Method) 2.25

Overall course attainment level 2.25

 Program Outcome Attainment (from Course)

Name of Faculty: Mrs.S.Arulmozhi AP/CSE Academic Year: 2023-24

Branch & Section: CSE Year: I
Principles Of
Course Name: Programming Semester:I
Languages

CO-PO mapping
PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2
CO1 3 2 2 2 2
CO2 3 2 2 2 1 2
CO3 3 2 2 2 2 2
CO4 3 1 2 2 1 2
CO5 2 1 1 2 2 1
CO6 3 2 2 2 2
Course 2.8 1.6 2.6 2 2 1.6 1.75

CO Course Outcome Attainment

2.25
CO1
2.25
CO2
2.25
CO3
2.25
CO4
2.25
CO5
CO6 2.25
Overall course attainment level 2.25

PO-ATTAINMENT
PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12
CO
Attainme
nt 2.10 1.20 1.95 1.50 1.50

CO contribution to PO - 33%, 67%, 100% (Level 1/2/3)

 ASSIGNMENTS AND ATTENDANCE REGISTER
Assignment-1 Script link:

https://drive.google.com/file/d/1kYVqBJsEJRGOykY2dYfZZf5ME8YgdvXx/view?usp=sharing

Assignment-2 Script link:

https://drive.google.com/file/d/1kYVqBJsEJRGOykY2dYfZZf5ME8YgdvXx/view?usp=sharing

Attendance Register Link:

https://drive.google.com/file/d/1wdBRAmHPXKK3dkthDOZhP1YBp-
mCG8c1/view?usp=sharing