DATA MINING AND BUSINESS INTELLIGENCE
- Course
- MISY542 - DATA MINING AND BUSINESS INTELLIGENCE
- Department
- Master of Management Information Systems - English - Master
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 0
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- -
- Prerequisite
- -
- Keywords
- -
Course Description
-
DATA MINING AND BUSINESS INTELLIGENCE
Evaluation Tools (Active Term)
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Course outcomes
No course outcomes have been defined yet.
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | Introduction |
| Week 2 | An Overview of Business Intelligence |
| Week 3 | Data Warehousing |
| Week 4 | Business Reporting, Visual Analytics, and Business, Performance Management |
| Week 5 | Introduction to Data Mining |
| Week 6 | Data Mining for Business Intelligence |
| Week 7 | Data in Data Mining |
| Week 8 | Midterm Exams |
| Week 9 | Midterm Exams |
| Week 10 | Project Presentations |
| Week 11 | Basic Data Classification |
| Week 12 | Cluster Analysis: Basic Concepts and Algorithms |
| Week 13 | Data Mining Processes |
| Week 14 | Data Mining Applications |
| Week 15 | Project Presentations |
Reference Books & Course Materials
- 01 Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner, 2nd Edition, Galit Shmueli; Nitin R. Patel; Peter C. Bruce
- 02 Business Intelligence: A Managerial Perspective on Analytics, 3/E, Ramesh Sharda, Dursun Delen, Efraim Turban
- 03 Data Mining Techniques and Applications , 1st Ed., Hongbo Du, Cengage Learning
- 04 Introduction to Data Mining: Pearson New International Edition, 1st Ed., Pang-Ning Tan; Michael Steinbach; Vipin Kumar, Pearson.
Learning Outcomes
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Program Outcomes
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