This course on Artificial Intelligence aims to introduce students to the fundamentals of AI, including state space search, neural networks, genetic algorithms, and knowledge representation. By the end of the course, students will be able to apply various search methods, game playing algorithms, and expert systems in real-world scenarios. The course teaches skills such as problem-solving, logical reasoning, and machine learning. The teaching method includes lectures, assignments, and assessments. This course is intended for students and professionals interested in gaining a foundational understanding of Artificial Intelligence.
Overview
Syllabus
COURSE LAYOUT
]]>Week Plan SUBJECT AI MOOC TITLE Introduction to Artificial Intelligence Week Title Modules covered in the Week Week 1 Introduction to AI and State space search 1,2,3 Week 2 Introduction to unguided and guided search 4,5,6 Week 3 Problems in search and solutions, Genetic algorithms 7,8 Week 4 Neural Networks, BPNN, learning process in BPNN 9,10,11 Week 5 Some other search methods and Admissibility 12,13,14,15 Week 6 Planning 16,17,18 Week 7 Game Playing 19,20 Week 8 REVISION AND ASSIGNMENT WEEK NONE Week 9 Minimax and other game playing algorithms 21,22,23 Week 10 Using predicate logic for Knowledge Representation 24,25 Week 11 Resolution and non-monotonic reasoning 26,27 Week 12 Strong methods for Knowledge Representation; Fuzzy logic and CD 28,29,30 Week 13 Scripts and Introduction to Expert systems 31,32,33 Week 14 Developing expert systems and Machine learning 34,35,36 Week 15 REVISION, ASSESSMENT and Evaluation NONE
Taught by
Prof. Bhushan Trivedi
