Data Mining Methods
Updated on
Course overview
- Provider
- Coursera
- Course type
- Free online course
- Level
- Intermediate
- Deadline
- Flexible
- Duration
- 23 hours
- Certificate
- Paid Certificate Available
- Course author
- Qin (Christine) Lv
-
Identify the core functionalities of data modeling in the data mining pipeline
Apply techniques that can be used to accomplish the core functionalities of data modeling and explain how they work.
Evaluate data modeling techniques, determine which is most suitable for a particular task, and identify potential improvements.
Description
This course covers the core techniques used in data mining, including frequent pattern analysis, classification, clustering, outlier analysis, as well as mining complex data and research frontiers in the data mining field. Data Mining Methods can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.
Course logo image courtesy of Lachlan Cormie, available here on Unsplash: https://unsplash.com/photos/jbJp18srifE
