Topic: Recordings | EES1137 Quantitative Applications for Data Analysis (Winter 2026)

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Topic outline

- Select activity 1. Introduction to the Linux command line I
  
  1. Introduction to the Linux command line I File
- Select activity 2. Introduction to the Linux command line II
  
  2. Introduction to the Linux command line II File
- Select activity 3. Introduction to R
  
  3. Introduction to R File
- Select activity 4. Vectors and data frames
  
  4. Vectors and data frames File
- Select activity 5. Lists, loops and conditional statements in R and 6. Functions in R
  
  5. Lists, loops and conditional statements in R and 6. Functions in R File
- Select activity 7. Scripts
  
  7. Scripts File
- Select activity 8. Version control - GIT
  
  8. Version control - GIT File
- Select activity 8. Coding best practices
  
  8. Coding best practices File
- Select activity 10. Distributions
  
  10. Distributions File
- Select activity 11. Hypothesis tests
  
  11. Hypothesis tests File
- Select activity 12. Linear models
  
  12. Linear models File
- Select activity 13. Visualization in R
  
  13. Visualization in R File
- Select activity 14. Introduction to Python
  
  14. Introduction to Python File
- Select activity 15. Loops and functions in Python
  
  15. Loops and functions in Python File
- Select activity 16. NumPy, SciPy and Visualization
  
  16. NumPy, SciPy and Visualization File
- Select activity 17. Introduction to Machine Learning
  
  17. Introduction to Machine Learning File
- Select activity 18. Resampling
  
  18. Resampling File
- Select activity 19. Classification
  
  19. Classification File
- Select activity 20. Unsupervised learning
  
  20. Unsupervised learning File
- Select activity 21. Monte Carlo methods
  
  21. Monte Carlo methods File
- Select activity 22. Feature selection
  
  22. Feature selection File
  
  This is a recording of a previous lecture. No lecture was given due to lack of attendance.
- Select activity 23. Neural networks
  
  23. Neural networks File
  
  This is a recording of a previous lecture. No lecture was given due to lack of attendance.
- Select activity 24. Ensemble methods
  
  24. Ensemble methods File