Academic Catalog


Course Code: 9010580
METU Credit (Theoretical-Laboratory hours/week): 3(3-0)
ECTS Credit: 8.0
Language of Instruction: English
Level of Study: Masters
Course Coordinator: Prof.Dr. NAZFE BAYKAL
Offered Semester: Fall or Spring Semesters.

Course Content

The course introduces principles and techniques of data mining and knowledge discovery. It emphasizes the advantages and disadvantages of using these methods in real world systems and provides hands-on experience. Its technical focus is on qualitative and quantitative knowledge based systems and learning systems. Topics include key issues of data mining and machine learning, decision trees, artificial neural networks, Bayesian learning, instance based learning, expert systems, fuzzy systems, and genetic algorithms.