CENG499 SPECIAL TOPICS: INTRODUCTION TO MACHINE LEARNING
| Course Code: | 5710499 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 6.0 |
| Department: | Computer Engineering |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Assoc.Prof.Dr. ŞEYDA ERTEKİN BOLELLİ |
| Offered Semester: | Fall Semesters. |
Course Objectives
Course Content
This course provides a broad introduction to machine learning. The topics include supervised and unsupervised learning, Bayesion inference/classification, regression, clustering, kernels and Support Vector Machines (SVM) and accompanying concepts such as model and feature selection, combining classifiers such as boosting, active learning, dimension reduction techniques.
Course Learning Outcomes
Program Outcomes Matrix
| Contribution |
| # | Program Outcomes | No | Yes |
| 1 | An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | | ✔ |
| 2 | An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | | ✔ |
| 3 | An ability to communicate effectively with a range of audiences | ✔ | |
| 4 | An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | ✔ | |
| 5 | An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | ✔ | |
| 6 | An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | | ✔ |
| 7 | An ability to acquire and apply new knowledge as needed, using appropriate learning strategies | | ✔ |
