Parallel Computing (CS473), Spring 2005, Spring 2006, Fall 2007

Peer-to-Peer Systems (CS474), Spring 2007 (introduced), Spring 2008

Computational Intelligence (CS457), Winter 2005 (introduced), Winter 2006, Winter 2007, Winter 2008

Artificial Intelligence (CS455), Spring 2004

Advanced Data Structures (CS302), Winter 2004, Summer 2004, Winter 2005, Winter 2008

Programming Fundamentals I (CS110), Winter 2004, Spring 2004, Spring 2005, Fall 2005, Fall 2006, Spring 2008

Programming Fundamentals II (CS111), Winter 2006, Summer 2006, Winter 2007

Algorithm Analysis (CS427), Fall 2003, Fall 2004, Fall 2007

Data Structures (CS301), Fall 2003, Spring 2004, Fall 2004, Spring 2005, Fall 2005, Spring 2006, Fall 2006, Spring 2007, Fall 2007, Spring 2008

Computer Programming with Engineering Applications (CS2073), Fall 1999, Spring 2000

Software Engineering (CS3773), Fall 1999

Discrete Mathematical Structures (CS3233), Spring 2000

Introduction to Artificial Neural Networks (CS4793), Spring 2000

Parallel/Distributed Computing Seminar (CSC8220), Winter 1999)

Parallel Computing (CSC7220), Fall 1998

Data Structures and Algorithm Analysis (CSC2200), Fall 1997, Fall 1998, Winter 1999

Problem Solving and Programming in C++ (CSC1100), Fall 1997, Winter 1998, Summer 1999

Introduction to Computer Science (CSC1000), Fall 1997, Winter 1998

Computational Intelligence, 1993 (introduced) to 1997, 2000 to 2002

Contents: Neural networks, genetic algorithms, fuzzy and neuro-fuzzy systems, swarm intelligence.

Level: Graduate.

Algorithms and Complexity, 1992 (introduced) to 1997, Spring 2003

Contents: Fundamental algorithms, algorithm analysis, data structures, NP-completeness, object-oriented design and implementations.

Level: Undergraduate-graduate.

Data Mining, 2000 (introduced) to 2003

Contents: Machine learning and neural networks for data mining, with applications in e-commerce. This course presents the state-of-the-art in knowledge-based neurocomputing. Meanwhile, it presents methods to encode prior knowledge, and to extract, refine and revise knowledge within a neurocomputing system.

Level: Master, PhD.

Parallel Algorithms and Architectures, 1994 (introduced) to 1997

Contents: Parallel computer architectures, parallel fundamental algorithms, parallel complexity.

Level: Graduate.

Neural Networks for Prediction, Winter 1997 (introduced)

Contents: Neural models used in time series prediction and dynamic system identification.

Level: Master.