IE460 INTRODUCTION TO DATA MINING
| Course Code: | 5680460 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 5.0 |
| Department: | Industrial Engineering |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Prof.Dr. CEM İYİGÜN |
| Offered Semester: | Fall and Spring Semesters. |
Course Objectives
Introduction to Data Mining course is a second level course in engineering data analysis and data mining. The emphasis is on understanding the application of a wide range of modern techniques to specific decision-making situations. Upon successful completion of the course, you should possess valuable practical analytical skills that will equip you with a competitive edge in almost any contemporary workplace. The course covers methods that are aimed at prediction, association, classification, and clustering. It also introduces optimization foundation of the data mining tehniques.
Course Content
Introduction to data mining .Data types. Classification Analysis: Rule Based, Nearest-Neighbour and Bayesian Classifiers, Support Vector Machines. Association Analysis: Rule Generation. Cluster Analysis: Center-based Clustering, Hiearchial , Density-based and Fuzzy Clustering. Cluster Validation, Anomaly Detection, Case studies.
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 | ✔ | |||
| 8 | An ability to design, analyze, operate, and improve integrated systems that produce and/or supply products and/or services in an effective, efficient, sustainable, and socially responsible manner | ✔ | |||
| 9 | An ability to apply critical reason and systems thinking in problem solving and systems design | ✔ | |||
| 10 | An ability to use scientific methods and tools (such as mathematical models, statistical methods and techniques) necessary for industrial engineering practice | ✔ | |||