Foundation Course
Business Analytics

using R

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Program Objective

This program is designed to equip professionals with the capabilities in extracting implicit, previously unknown and potentially useful knowledge from large datasets

Program Benefits

The participants will acquire the knowledge required for

  • Data exploration and visualization
  • Preprocessing and transformations
  • Supervised (predictive modeling) and unsupervised learning techniques
  • Interpretation and validation of results
  • Hands-on experience on the usage of open source packages like R and R Studio


  • Any science, commerce or engineering graduate can participate in the program
  • The knowledge of a programming language is desirable but not necessary 
  • The examination will be conducted at the end of the course and successful candidates will be issued the certificate

Course Content

  1. Introduction to analytics
  2. Data exploration and visualization techniques
  3. Inferential Statistics (Test of Hypothesis, ANOVA, etc)
  4. Linear and polynomial regression
  5. Dummy variable regression
  6. Logistic regression
  7. Classification and regression tree
  8. Regression splines 
  9. Artificial neural networks 
  10. Naïve Bayes classifier
  11. K nearest neighbor method
  12. Support vector machines
  13. Leave one out and k fold cross-validation methods
  14. Factor analysis
  15. Cluster analysis 
  16. Association rule mining