CENG414 INTRODUCTION TO DATA MINING
| Course Code: | 5710414 |
| 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: | Prof.Dr. PINAR KARAGÖZ |
| Offered Semester: | Fall Semesters. |
Course Objectives
At the end of the course students will be able to have an understanding of data mining techniques, and can apply them to real-life problems.
Related Program Educational Objectives are:
1. design, construct and operate software-intensive systems.
2. analyze problems from a computational viewpoint, propose algorithmic solutions, and implement them correctly and efficiently.
Course Content
Concepts of data mining. Data preprocessing. Data warehousing and OLAP for data mining. Association, correlation, and frequent pattern analysis. Classification. Cluster and outlier analysis. Mining time-series and sequence data. Text mining and web mining. Visual data mining. Industry efforts and social impacts. Applications of data mining.
Course Learning Outcomes
Learning Outcomes:
an ability to apply knowledge of mathematics, science, and engineering
an ability to design and conduct experiments, as well as to analyze and interpret data
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 | ✔ | |||