Course: MSC1090 Introduction to Computational Biostatistics with R (Fall 2025)

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Select section General

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General

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- Select activity Course Description
  
  MSC1090 Introduction to Computational Biostatistics with R (Fall 2025)
  The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language. Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data. Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
  Classes will be held Tuesdays 10:00-11:30am in ESB142, and Thursdays 12:00-1:30pm in MS2173.
  Students willing to take the course as part of their graduate program must enrol through Acorn. This course is part of the IMS graduate program.
  Start date: 9 Sep. 2025
  End date: 27 Nov. 2025
  Scientific Computing Credits: 8
  Data Science Credits: 28
  Events:
  Assignment 1 is due - Thursday, 18 September, 11:59 PM
  Assignment 2 is due - Thursday, 25 September, 11:59 PM
  Assignment 3 is due - Thursday, 2 October, 11:59 PM
  A full list of course events can be found here.
- Select activity Software requirements
  
  Software requirements Page
- Select activity Course evaluation
  
  Course evaluation Page
- Select activity Student forum
  
  Student forum
- Select activity Announcements
  
  Announcements Forum
Select section Lectures

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Lectures
- 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
  
  5. Lists, loops and conditional statements in R File
- Select activity 6. Functions in R
  
  6. Functions in R File
- Select activity 7. Scripts
  
  7. Scripts File
- Select activity 8. Version Control System - Git
  
  8. Version Control System - Git File
- Select activity 9. Coding Best Practices
  
  9. Coding Best Practices File
- Select activity 10. Distributions
  
  10. Distributions File
- Select activity 11. Hypothesis tests
  
  11. Hypothesis tests File
- Select activity 12. Visualization
  
  12. Visualization File
- Select activity 13. ANOVA
  
  13. ANOVA File
- Select activity 14. Linear models
  
  14. Linear models File
- Select activity 15. Generalized linear models
  
  15. Generalized linear models File
- Select activity 16. Resampling
  
  16. Resampling File
- Select activity 17. Mixed-effects models
  
  17. Mixed-effects models File
- Select activity 18. Survival analysis
  
  18. Survival analysis File
- Select activity 19. Classification I
  
  19. Classification I File
- Select activity 20. Classification II
  
  20. Classification II File
- Select activity 21. Unsupervised learning
  
  21. Unsupervised learning File
- Select activity 22. Neural networks
  
  22. Neural networks File
- Select activity 23. Ensemble methods
  
  23. Ensemble methods File
- Select activity 24. High-Performance Computing in R
  
  24. High-Performance Computing in R File
Select section Recordings

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Recordings
- 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 conditionals in R
  
  5. Lists, loops and conditionals in R File
- Select activity 6. Functions in R
  
  6. Functions in R File
- Select activity 7. Scripts
  
  7. Scripts File
- Select activity 8. Version control system - Git
  
  8. Version control system - Git File
- Select activity 9. Coding Best Practices
  
  9. Coding Best Practices File
- Select activity 10. Distributions
  
  10. Distributions File
- Select activity 11. Hypothesis tests
  
  11. Hypothesis tests File
- Select activity 12. Visualization
  
  12. Visualization File
- Select activity 13. ANOVA
  
  13. ANOVA File
- Select activity 14. Linear models
  
  14. Linear models File
- Select activity 15. Generalized linear models
  
  15. Generalized linear models File
- Select activity 16. Resampling
  
  16. Resampling File
- Select activity 17. Mixed-effects models
  
  17. Mixed-effects models File
- Select activity 18. Survival Analysis
  
  18. Survival Analysis File
- Select activity 19. Classification I
  
  19. Classification I File
- Select activity 20. Classification II
  
  20. Classification II File
- Select activity 21. Unsupervised learning
  
  21. Unsupervised learning File
- Select activity 22. Neural networks
  
  22. Neural networks File
- Select activity 23. Ensemble methods
  
  23. Ensemble methods File
- Select activity 24. High-Performance Computing in R
  
  24. High-Performance Computing in R File
Select section Assignments

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Assignments
- Select activity Assignment 1
  
  Assignment 1
  
  Opened: Thursday, 11 September 2025, 1:00 PM
  
  Due: Thursday, 18 September 2025, 11:59 PM
- Select activity Assignment 2
  
  Assignment 2
  
  Opened: Thursday, 18 September 2025, 1:00 PM
  
  Due: Thursday, 25 September 2025, 11:59 PM
- Select activity Assignment 3
  
  Assignment 3
  
  Opened: Thursday, 25 September 2025, 1:00 PM
  
  Due: Thursday, 2 October 2025, 11:59 PM
- Select activity Assignment 4
  
  Assignment 4
  
  Opened: Thursday, 2 October 2025, 1:00 PM
  
  Due: Thursday, 9 October 2025, 11:59 PM
- Select activity Assignment 5
  
  Assignment 5
  
  Opened: Thursday, 9 October 2025, 1:00 PM
  
  Due: Thursday, 23 October 2025, 11:59 PM
- Select activity Assignment 6
  
  Assignment 6
  
  Opened: Thursday, 23 October 2025, 1:00 PM
  
  Due: Thursday, 30 October 2025, 11:59 PM
- Select activity Assignment 7
  
  Assignment 7
  
  Opened: Thursday, 30 October 2025, 12:00 AM
  
  Due: Thursday, 6 November 2025, 11:59 PM
- Select activity Assignment 8
  
  Assignment 8
  
  Opened: Thursday, 6 November 2025, 1:00 PM
  
  Due: Thursday, 13 November 2025, 11:59 PM
- Select activity Assignment 9
  
  Assignment 9
  
  Opened: Thursday, 13 November 2025, 1:00 PM
  
  Due: Thursday, 20 November 2025, 11:59 PM
- Select activity Assignment 10
  
  Assignment 10
  
  Opened: Thursday, 20 November 2025, 1:00 PM
  
  Due: Thursday, 27 November 2025, 11:59 PM
- Select activity Assignment 11 - Make-up
  
  Assignment 11 - Make-up
  
  Opened: Thursday, 27 November 2025, 1:00 PM
  
  Due: Thursday, 4 December 2025, 11:59 PM

Topic outline

General

MSC1090 Introduction to Computational Biostatistics with R (Fall 2025)

Lectures

Recordings

Assignments