Architecture.

ANNA UNIVERSITY, CHENNAI
NON- AUTONOMOUS AFFILIATED COLLEGES
REGULATIONS 2021
CHOICE BASED CREDIT SYSTEM
B.TECH. ARTIFICIAL INTELLIGENCE AND DATA SCIENCE


I. PROGRAM EDUCATIONAL OBJECTIVES (PEOs)

Graduates can
1. Utilize their proficiencies in the fundamental knowledge of basic sciences, mathematics,
Artificial Intelligence, data science and statistics to build systems that require management
and analysis of large volumes of data.
2. Advance their technical skills to pursue pioneering research in the field of AI and Data
Science and create disruptive and sustainable solutions for the welfare of ecosystems.
3. Think logically, pursue lifelong learning and collaborate with an ethical attitude in a
multidisciplinary team.
4. Design and model AI based solutions to critical problem domains in the real world.
5. Exhibit innovative thoughts and creative ideas for effective contribution towards economy
building.

II.PROGRAM OUTCOMES (POs)

PO# Graduate Attribute
1 Engineering knowledge: Apply the knowledge of mathematics, science, engineering
fundamentals, and an engineering specialization to the solution of complex engineering
problems.
2 Problem analysis: Identify, formulate, review research literature, and analyze complex
engineering problems reaching substantiated conclusions using first principles of
mathematics, natural sciences, and engineering sciences.
3 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.
4 Conduct investigations of complex problems: Use research-based knowledge
and research methods including design of experiments, analysis and interpretation of data,
and synthesis of the information to provide valid conclusions.
5 Modern tool usage: Create, select, and apply appropriate techniques, resources, and
modern engineering and IT tools including prediction and modeling to complex engineering
activities with an understanding of the limitations.
6 The engineer and society: Apply reasoning informed by the contextual knowledge to
assess societal, health, safety, legal and cultural issues and the consequent responsibilities
relevant to the professional engineering practice.
7 Environment and sustainability: Understand the impact of the professional engineering

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, solutions in societal and environmental contexts, and demonstrate the knowledge of, and need
for sustainable development.
8 Ethics: Apply ethical principles and commit to professional ethics and responsibilities and
norms of the engineering practice.
9 Individual and team work: Function effectively as an individual, and as a member or
leader in diverse teams, and in multidisciplinary settings.
10 Communication: Communicate effectively on complex engineering activities with the
engineering community and with society at large, such as, being able to comprehend and write
effective reports and design documentation, make effective presentations, and give and receive
clear instructions.
11 Project management and finance: Demonstrate knowledge and understanding of the
engineering and management principles and apply these to one’s own work, as a member and
leader in a team, to manage projects and in multidisciplinary environments.

12 Life-long learning: Recognize the need for, and have the preparation and ability to
engage in independent and life-long learning in the broadest context of technological change.

III. PROGRAM SPECIFIC OUTCOMES (PSOs)

Graduates should be able to:

1. evolve AI based efficient domain specific processes for effective decision making in several
domains such as business and governance domains.
2. arrive at actionable Foresight, Insight, hindsight from data for solving business and
engineering problems
3. create, select and apply the theoretical knowledge of AI and Data Analytics along with
practical industrial tools and techniques to manage and solve wicked societal problems
4. develop data analytics and data visualization skills, skills pertaining to knowledge acquisition,
knowledge representation and knowledge engineering, and hence be capable of coordinating
complex projects.
5. able to carry out fundamental research to cater the critical needs of the society through
cutting edge technologies of AI.




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, Mapping of Course Outcome and Programme Outcome

Year Sem Course name PO PSO

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3
Induction Programme
I
I Professional English - I 1.6 2.2 1.8 2.2 1.5 3 3 3 1.6 3 3 3 - - -
Matrices and Calculus 3 3 1 1 0 0 0 0 2 0 2 3 - - -
Engineering Physics 3 3 1.6 1.2 1.8 1 - - - - - 1 - - -
Engineering Chemistry 2.8 1.3 1.6 1 - 1.5 1.8 - - - 1.5 - - -
Problem Solving and
2 3 3 3 2 - - - - - 2 2 3 3
Python Programming
தமிழர் மரபு
/Heritage of Tamils
Problem Solving and
Python Programming 2 3 3 3 2 - - - - - 2 2 3 3 -
Laboratory
Physics and Chemistry 3 2.4 2.6 1 1
Laboratory
2.6 1.3 1.6 1 1 1.4 1.8 - - - - 1.3 - - -

English Laboratory $ 3 3 3 3 1 3 3 3 3 3 3 3 - - -

II Professional English - II 3 3 3 3 2.75 3 3 3 2.2 3 3 3 - - -
Statistics and
3 3 1 1 1 0 0 0 2 0 2 3 - - -
Numerical Methods
Physics for Information
3 1.3 2 1.3 2.3 1 1.3 - - - - 2 - - -
Science
Basic Electrical and 2 1.8 1 - - - - 1 - - - 2 - - 1
Electronics Engineering
3 1 2 - 2 - - - - 3 - 2 2 2 -
Engineering Graphics

Data Structures Design

தமிழரும்
ததொழில் நுட்பமும்
/Tamils and
Technology
Engineering Practices 3 2 - - 1 1 1 - - - - 2 2 1 1
Laboratory
Data Structures Design
Laboratory
Communication
2.4 2.8 3 3 1.8 3 3 3 3 3 3 3 - - -
Laboratory / Foreign
Language $
1 3 2 1 - - - - - 1 - - - - -
II Iii Discrete Mathematics
Digital Principles and
3 3 3 3 1.8 1.6 1 1 1 1 1.6 2.6 1.4 2.6 1.6
Computer Organization
Database Design and
2 2 2 2 1 - - - 2 2 1 1 2 2 2
Management
Design and Analysis of
3 2 2 2 2 - - - 2 2 2 2 2 2 2
Algorithms
3

, Data Exploration and
Visualization 2 1 2 2 1 - - - 2 2 2 2 2 2 2

Artificial Intelligence 2 1 2 2 1 - - - 2 2 2 2 2 2 2
Database Design and
Management 2 2 2 2 1 - - - 2 2 2 2 2 2 2
Laboratory
Artificial Intelligence
2 1 2 2 1 - - - 2 2 2 2 2 2 2
Laboratory
Professional
Development$
Probability and
IV 3 3 1 1 0 0 0 0 2 0 0 2
Statistics
Operating Systems 2 2 2 2 1 - - - 2 2 2 2 2 1 2
Machine Learning 2 2 3 2 2 - - - 2 2 2 2 2 2 1
Fundamentals of Data
1 1 2 2 2 - - - 3 2 2 2 3 2 1
Science and Analytics
Computer Networks 2 2 2 2 2 - - - 2 2 2 1 2 2 2
Environmental
Sciences and 2.8 1.8 1 1 - 2.2 2.4 - - - - 1.8 - - -
Sustainability
Data Science and
2 2 1 2 2 - - - 2 2 2 2 2 2 1
Analytics Laboratory
Machine Learning
2 2 2 2 2 - - - 2 2 2 2 2 2 2
Laboratory
Deep Learning 2.8 2.4 2 2.4 2.2 - - - 1.6 2.4 1.4 2.4 2 1.8 2.6
III V
Data and Information
2.4 2.6 2.4 2.2 1.5 - - - 1.4 2.2 1.2 2.2 1.8 2 1.6
Security
Distributed Computing 1.8 2.4 1.8 2.4 2 - - - 2.6 2.2 2.2 1.6 2 1.8 1.6
Big Data Analytics 2.8 3 2.8 2.8 2.8 - - - 2.2 1.8 2.6 2 2.2 2.8 2.6
Deep Learning
2.6 2.6 1.6 2 1.4 - - - 2 2.4 2.2 1.6 2.4 2.8 2
Laboratory
Summer internship

Embedded Systems
VI 2.6 2 3 2.4 1.5 - - - 1 2.2 2.2 2.4 2.2 1.6 2.6
and IoT
Human Values and
IV VII Ethics
Summer internship
Project Work /
VIII Internship
1 - low, 2 - medium, 3 - high, ‘-' - no correlation




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