Course Language:
English
Course Objectives:
The aim of this course is to provide students the knowledege about the basic techniques and methodologies of machine learning and abilities to apply machine learning methods on practical problems. |
Course Content:
Basic concepts and techniques of machine learning. Supervised learning tecniques. Concept and Decision Tree Learning. Bayesian approach in machine learning. Evolutionary approach and genetic programming. Neural Networks, Support Vector Machines and reinforcement learning. Unsupervised machine learning and clustering. |
Teaching Methods:
Teaching Methods: 1: Lecture, 2: Discussion, 3: Seminar, 4: Research, 5: Simulation/Case Study/Role Playing, 6: Problem Session, 7: Invited Lecturer
Assessment Methods:
Assessment Methods: A: Exam, B: Assignment, C: Presentation, D: Research, E: Debate, F: Quiz, G: Participation