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ANLY600 - Data Mining
Course Details
Course Code: ANLY600 Course ID: 4875 Credit Hours: 3 Level: Graduate
This course covers data mining using the R programming language. It offers hands on experience approach through a learn-by-doing-it strategy. It further integrates data mining topics with applied business analytics to address real world data mining cases. It continues the examination of the role of “Data Mining in R”, and review statistics techniques in prescriptive analytics, and some predictive analytics. Additionally, some standard techniques and excel functions will be also covered.
Course Schedule
| Registration Dates | Course Dates | Session | Weeks |
|---|---|---|---|
| 04/27/20 - 10/02/20 | 10/05/20 - 11/29/20 | Fall 2020 Session B | 8 Week session |
| 07/27/20 - 01/01/21 | 01/04/21 - 02/28/21 | Winter 2021 Session B | 8 Week session |
Current Syllabi
After successfully completing this course, you will be able to
- LO 1: Demonstrate advanced knowledge of data mining concepts and techniques.
- LO 2: Apply the techniques of clustering, classification, association finding, feature selection and visualization on real world data
- LO 3: Determine whether a real world problem has a data mining solution
- LO 4: Apply data mining software and toolkits in a range of applications
- LO 5: Set up a data mining process for an application, including data preparation, modelling and evaluation
- LO 6: Demonstrate knowledge of the ethical considerations involved in data mining.
| Name | Grade % |
|---|---|
| Discussions | 28.00 % |
| Week 1 Discussion | 3.50 % |
| Week 2 Discussion | 3.50 % |
| Week 3 Discussion | 3.50 % |
| Week 4 Discussion | 3.50 % |
| Week 5 Discussion | 3.50 % |
| Week 6 Discussion | 3.50 % |
| Week 7 Discussion | 3.50 % |
| Week 8 Discussion | 3.50 % |
| Assignments | 72.00 % |
| Week 1 Assignment | 12.00 % |
| Week 2 Assignment | 12.00 % |
| Week 3 Assignment | 12.00 % |
| Week 5 Assignment | 12.00 % |
| Week 6 Assignment | 12.00 % |
| Week 7 Assignment | 12.00 % |
Required Course Textbooks:
Data Mining and Business Analytics with R
Johannes Ledolter
URL: https://www.vitalsource.com/referral?term=9781118593639
Additional Resources
Additional resources will be provided in the class.
Web Sites
In addition to the required course texts, the following public domain web sites are useful. Please abide by the university’s academic honesty policy when using Internet sources as well. Note web site addresses are subject to change.
|
Site Name |
Web Site URL/Address |
|
Machine Learning Videos |
|
|
OnePageR |
http:// togaware.com/onepager/ |
|
Data Mining Resources |
http://www.ngdata.com/data-mining- resources/ |
|
Top Free Data Mining Software |
http://www.predictiveanalyticstoday.com/top- free-data-mining-software/ |
| Book Title: | Data Mining and Business Analytics with R - eBook available in the APUS Online Library |
| ISBN: | 9781118447147 |
| Publication Info: | Wiley |
| Author: | Johannes Ledolter |
| Unit Cost: | $104.60 |
Previous Syllabi
Not current for future courses.