No other field in computer science has higher visibility (and expectation, and disappointment) than artificial intelligence to the general population. This course covers the basic components of artificial intelligence as we know it, namely search, optimization, logic and machine learning. You should be able to build simple but interesting AI systems at the end of the semester.
Here you will find administrative information for the Winter 1396.
<![if !supportLists]> <![endif]> Instructor: Dr. Mohsen Afsharchi, afsharchi at znu.ac.ir
<![if !supportLists]> <![endif]> Lectures: Sat 8-9:30, Tue 8-9:30
<![if !supportLists]> <![endif]> Prerequisites: Clear understanding of common data structures, algorithms and standard programming
The required textbook for this course is:
<![if !supportLists]> <![endif]>Artificial Intelligence: A Modern Approach (Third Edition), by Stuart J. Russell, Peter Norvig, Prentice Hall 2009 .
A supplementary textbook (recommended, but not required) is:
<![if !supportLists]> <![endif]>Artificial Intelligence: A New Synthesis, by Nils J. Nilsson. Morgan Kaufmann 1999.
Lecture material will be drawn from both textbooks, as well as from some of the recent online AI literature.
Overfitting Example (PDF)
1- Course Project 1 (Search)
2- Home Work 1 (HW)
Project 1: Mixture of Gaussians for Classification and Non-linear Regression (PDF) (Data set a , JPG) (Data set b , JPG) Project 2: Simple CNN for Persian font Recognition (PDF)
Here is an ad hoc collection of relevant AI links and interesting tidbits. If you know of other good stuff to share with your classmates here, please let me know, and I will try to add it.