CPC251: Course Description
The first part of the course introduces methods of learning from data and explains the concepts behind various machine learning techniques. The course covers the basics of both supervised and unsupervised learning paradigms. Students will learn to identify the characteristics of datasets, select features and machine learning algorithms, evaluate the performance of the machine learning models, and work on how to get the best performance. Students will also practice to construct machine learning models by integrating machine learning libraries and tools for various datasets and case studies. The second part of the course introduces the various techniques of computational intelligence. Various knowledge sources that are relevant to computational intelligence problems will be discussed. Students will also be exposed to advanced knowledge representation and reasoning approaches.

At the end of this course the students will be able to:

Explain concepts, theories and implementation of machine learning and computational intelligence techniques.
Construct predictive models by integrating machine learning and computational intelligence libraries and tools.
Analyze problems and propose solutions using machine learning and computational intelligence techniques.

Course Lecturers:

Dr. Mohd Halim Mohd Noor @ halimnoor@usm.my
Dr. Mohd Nadhir Ab Wahab @ mohdnadhir@usm.my