Data Mining in Business Analytics

The project contains a lecture course “Data Mining in Business Analytics”, materials of workshops and code. It is devoted to algorithms of data analysis and their applications. It includes practical examples from business and financial sector. The compete set of materials are here. Use “save link as” if your browser does not open these PDFs.

  1. Course syllabus
  2. Introduction to Data Analysis
  3. Written exam: the white sheet and the full draft version
  4. Examples of Data Mining problems (MIT Open courseware)
  5. Introduction, quantitative modelling
  6. Examples of Data Mining problems (MIT Open courseware)
  7. MSExcell Linear regression and Prices forecasting
  8. MSExcell k-NN Forecasting example
  9. Google spreadsheet commands
  10. DMBA data repository
  11. Indicators and decision making part1 and part2
  12. Pairwise comparison
  13. Kemeny-Young method (wiki)
  14. Pareto optimal front part 1 and part 2
  15. Risk analysis and banking scoring and risk analysis flowchart
  16. 1) Weight of evidence 2) Cohort analysis 3) Stability report 4) Scorecard planning (SAS)
  17. Logistic regression calculator (Statpages)
  18. Atoms for Scilab
  19. Data preparation and General statistics (Uni.-Princeton )
  20. Sociological data processing
  21. Verification of scoring models
  22. Classification and decision trees
  23. Forecasting of goods consumption
  24. Nonparametric regression
  25. Forecasting of energy consumption/stock option price
  26. The next day energy consumption forecasting
  27. Management and standards, CRISP-DM
  28. IDEF0 diagrams
  29. Show1Show2, and Memos
  30. Resume

Vadim Victor

Vadim V. Strijov, Data Analysis & Machine Learning professor at the FRCCSC of the RAS, Doctor of Physics and mathematics sciences

You may also like...