About the Course
This course offers a comprehensive introduction to Artificial
Intelligence (AI) in Tamil,
designed to provide students with both theoretical knowledge and practical
skills. It covers fundamental AI concepts, search strategies, game-playing
algorithms, knowledge representation, reasoning under uncertainty, planning,
and constraint satisfaction. By the end of this course, students will be
equipped to design intelligent systems and understand AI’s role in solving
real-world problems.
Prerequisites
| Course Status : | Upcoming |
| Course Type : | Core |
| Language for course content : | Tamil |
| Duration : | 12 weeks |
| Category : |
|
| Credit Points : | 4 |
| Level : | Undergraduate |
| Start Date : | 14 Jan 2026 |
| End Date : | 30 Apr 2026 |
| Enrollment Ends : | 28 Feb 2026 |
| Exam Date : | |
| Translation Languages : | Tamil |
| NCrF Level : | 4.5 |
|
Week |
Topic |
Key
Focus |
|
1 |
Introduction
to AI |
Definition
of AI, Turing Test, History of AI |
|
2 |
Introduction
to AI |
Problem-Solving
and Search Strategies |
|
3 |
Informed
and Local Search |
Heuristic
Techniques: A*, Greedy Search |
|
4 |
Informed
and Local Search |
Optimization
Methods: Hill Climbing, Genetic Algorithms |
|
5 |
Game
Playing & Advanced Search |
Game
Trees, Minimax Algorithm |
|
6 |
Game
Playing & Advanced Search |
Alpha-Beta
Pruning, Advanced Searching Techniques |
|
7 |
Knowledge
Representation |
Ontologies,
Predicate Logic, Reasoning Methods |
|
8 |
Uncertain
Knowledge |
Probability
Basics, Bayesian Networks |
|
9 |
Uncertain
Knowledge |
Applications
of Uncertain Reasoning |
|
10 |
Planning |
STRIPS
Language, Forward and Backward Planning, Heuristics |
|
11 |
Planning |
Planning
vs Scheduling |
|
12 |
Constraint
Satisfaction Problems (CSPs) |
CSP
Fundamentals, Constraint Graphs, Backtracking, Heuristics |
1.
Elaine Rich, Kevin Knight (2008), Shivsankar B
Nair, Artificial Intelligence, Third Edition, Tata McGraw Hill Publication
Dr. K. Kavitha, Ph.D. is an Assistant Professor in the Department of Computer Science, Mother Teresa
Women’s University, Kodaikanal. She has over 18 years of teaching and 12
years of research experience, and holds a Ph.D. in Computer Science from Madurai Kamaraj University. Dr. Kavitha has published numerous research
papers in reputed journals and conferences and guided several Ph.D. and M.Phil.
scholars. Her research interests include Data Mining, Data Analytics, Deep Learning, and Cloud Computing,
with a focus on data-driven healthcare
systems and secure computing.
She has completed funded projects
under ICMR, ICSSR, and SIRD, and
is currently undertaking a research
project under IKS funded support (AICTE). She is also a Life Member of the International Association
of Engineers (IAENG).
Dr. Kavitha அவர்களுக்கு 18 ஆண்டுகளுக்கு மேலான கற்பித்தல் அனுபவமும், 12 ஆண்டுகளுக்கு மேலான ஆராய்ச்சி அனுபவமும் உள்ளது. அவர் தனது Ph.D. in Computer Science பட்டத்தை Madurai Kamaraj University யில் பெற்றார்.அவரது ஆராய்ச்சி துறைகள் Data Mining, Data Analytics, Deep Learning, Cloud Computing ஆகியவற்றை உள்ளடக்கியவை, குறிப்பாக data-driven healthcare systems மற்றும் secure computing மீது கவனம் செலுத்துகின்றன.அவர் ICMR, ICSSR, SIRD ஆகிய அமைப்புகளின் நிதி உதவியுடன் பல திட்டங்களை நிறைவேற்றியுள்ளார். தற்போது அவர் AICTE-IKS funded project ஒன்றை மேற்கொண்டு வருகிறார். பல சர்வதேச இதழ்களில் கட்டுரைகள் வெளியிட்டதுடன், பல Ph.D. மற்றும் M.Phil. மாணவர்களை வழிநடத்தியுள்ளார். Dr. Kavitha அவர்கள் International Association of Engineers (IAENG) இன் Life Member ஆவார்.
The final evaluation for the course will be based on two
components:
30% from In-Course
Assessment (assignments, quizzes,
internal tests, etc.)
70% from the End-Term
Proctored Examination
To qualify for
the course certificate, participants
must secure a minimum of 40% marks separately in both components — the In-Course Assessment and the End-Term Exam. Only candidates meeting these criteria will
be considered pass and eligible
to receive the course completion certificate.
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