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Course Details

 

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 Start Month Session Weeks
07/25/2022 - 12/30/2022 01/02/2023 - 02/26/2023 January Winter 2023 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.
NameGrade %
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 2 Assignment 14.40 %
Week 3 Assignment 14.40 %
Week 5 Assignment 14.40 %
Week 6 Assignment 14.40 %
Week 7 Assignment 14.40 %

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.
Book Title:Data Mining for Business Analytics: Concepts, Techniques, and Applications in R *Note: the price provided is for the VitalSource eBook
ISBN:9781118879368
Publication Info:Wiley
Author:Shmueli, G. Peter C. Bruce; Inbal Yahav; Nitin R. Patel;
Unit Cost:$145.39
Electronic ISBN:9781118879368
Electronic Unit Cost:$145.39
 
Book Title:Data Mining and Business Analytics with R (Ebook available through the APUS Online Library)
ISBN:9781118447147
Publication Info:Wiley Lib
Author:Johannes Ledolter
Unit Cost:$104.60
 

Previous Syllabi

Not current for future courses.