Artificial IntelligenceThis course aims to expose students to concepts and techniques that enable them to build smart applications including search strategies, agents, machine learning, planning, knowledge representation reasoning, lexical semantics and linguistic resources, information retrieval, natural language processing and computational linguistics. Course Outline |
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Part I: Problem Solving by Search
Introduction to Artificial Intelligence Part II : Machine Learning
Part III : Natural Language Processing
Part VI : Knowledge and Reasoning
Topics: {Planning, Fuzzy logic and Probabilistic Reasoning, Decision Making, Constraint Satisfaction, NLP topics, History of Logic}.
Every three students will select one of these topics and will be given 25 minutes to present it in front of all students.
Students will be evaluated based on: (i) their understanding of the topic and (ii) how much other students understood them.
Every three student should write a synthesis paper (6-10 pages) about a research topic that will be assigned
to them. Students are expected to read at least three recent articles related to the course topics;
and summarize and criticize them. Discussion and guidance will be provided during the course.
Invited Lectures
Textbook
Stuart Russell and Peter Norvig: Artificial Intelligence: A Modern Approach . Prentice Hall, 3rd Edition
Stuart Russell and Peter Norvig: Artificial Intelligence: A Modern Approach . Prentice Hall, 3rd Edition