Artificial Intelligence

56 contact hours (28 hours for lecture&discussion, 28 hours for lab sessions) 44 hours for preparing and documenting in-class and lab assignments, 50 hours for reviewing classes and preparing for the exam.

Foundations of computer science and basic programming skills. Some basic familarity with calculus, linear algebra, and logic.

Students who successfully complete this module will be able to:

1. Describe the main techniques to create intelligent machines.
2. Use relevant methods for representing knowledge and reasoning about it.
3. Apply machine learning techniques to data sets.

Introduction to fundamental techniques of artificial intelligence, including formalisms for representing knowledge and reasoning about it, methods for searching and planning, and approaches to machine learning.

Slides, notes, white board, video clips.

Standard texts on artificial intelligence, such as:

• Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach (Third Edition). Prentice-Hall, Upper Saddle River, New Jersey, 2010.
• Wolfgang Ertel. Introduction to Artificial Intelligence, Springer, 2011.
• Ivan Bratko. Prolog: Programming for Artificial Intelligence (Third Edition). Addison-Wesley, Readings, Massachusetts, 2000.
• Stephen Marsland. Machine Learning: An Algorithmic Perspective. CRC Press, Boca Raton, Florida, 2009.