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Objectives:
Artificial Intelligence (AI) and accompanying tools and techniques bring transformational
changes in the world. Machines capability to match, and sometimes even surpass human
capability, make AI a hot topic in Computer Science. This course aims to introduce the learner to
this interesting area.
Expected Learning Outcomes:
After completion of this course, learner should get a clear understanding of AI and different search
algorithms used for solving problems. The learner should also get acquainted with different
learning algorithms and models used in machine learning.
Unit I
What Is AI: Foundations, History and State of the Art of AI.
Intelligent Agents: Agents and Environments, Nature of Environments,
Structure of Agents.
Problem Solving by searching: Problem-Solving Agents, Example Problems,
Searching for Solutions, Uninformed Search Strategies, Informed (Heuristic)
Search Strategies, Heuristic Functions.
15L
Unit II
Learning from Examples: Forms of Learning, Supervised Learning, Learning
Decision Trees, Evaluating and Choosing the Best Hypothesis, Theory of
Learning, Regression and Classification with Linear Models, Artificial Neural
Networks, Nonparametric Models, Support Vector Machines, Ensemble
Learning, Practical Machine Learning
15L
Unit III
Learning probabilistic models: Statistical Learning, Learning with Complete
Data, Learning with Hidden Variables: The EM Algorithm. Reinforcement
learning: Passive Reinforcement Learning, Active Reinforcement Learning,
Generalization in Reinforcement Learning, Policy Search, Applications of
Reinforcement Learning.
15L
Textbook(s):
1) Artificial Intelligence: A Modern Approach, Stuart Russell and Peter Norvig,3rd Edition,
Pearson, 2010.
Additional Reference(s):
1) Artificial Intelligence: Foundations of Computational Agents, David L Poole,Alan K.
Mackworth, 2nd Edition, Cambridge University Press ,2017.
2) Artificial Intelligence, Kevin Knight and Elaine Rich, 3rd Edition, 2017
3) The Elements of Statistical Learning, Trevor Hastie, Robert Tibshirani and Jerome Friedman,
Springer, 2013