Schedule

Week 1 – Welcome & Introduction (05.04 - 11.04)

• Slides:
  • Welcome - HTML | PDF
  • First tour of R & RStudio - HTML | PDF
• Screencasts:
  • Welcome & Course Intro
  • First tour of R & RStudio
• Exercise: Ex 1
• Quiz: No quiz this week
• Additional material: No additional reading this week

Week 2 – Visualizing data with ggplot2 (12.04 - 18.04)

• Slides:
  • Introduction to ggplot2 - HTML | PDF
  • Effective visualizations - HTML | PDF
• Screencasts:
  • Intro to ggplot2
  • Visualizing numerical and categorical data
  • Tips for effective vizualizations
• Exercise:
  • Ex 2
  • Code-along
• Quiz: Q 1
• Additional material:
  • R4DS chapters:
    • Data Visualization
    • Exploratory Data Analysis
    • Graphics for communication
  • ggplot2 cheat sheet
  • Official ggplot2 book
  • Curated list of ggplot2 resources and extensions
  • Keynote talk: Alberto Cairo - How Charts Lie: Getting Smarter About Visual Information

Week 3 – The Tidyverse (19.04 - 25.04)

• Slides: The Tidyverse - HTML | PDF
• Screencasts:
  • Tidyverse intro & dplyr
  • Join functions
  • tidyr
  • readr&tibble
• Exercise: Ex 3 Code-along
• Quiz: Q 2
• Additional material:
  • R4DS chapters:
    • Data transformation
    • Tibbles
    • Data import
    • Tidy data
    • Relational data
    • Pipes.
  • Cheat sheets:
    • dplyr
    • Data Import (readr & tidyr)

Week 4 – R Markdown (26.04 - 02.05)

• Slides: R Markdown - HTML PDF
• Screencasts: R Markdown
• Exercise: Ex 4; no code-along this week
• Quiz: Q 3
• Additional material:
  • R4DS chapters:
    • R Markdown
    • R Markdown formats
    • R Markdown workflow
  • Quick Markdown tutorial
  • R Markdown cheat sheet
  • RStudio’s R Markdown reference guide
  • RStudio’s R Markdown Get Started Tutorial
  • List of all available Knitr chunk options
  • Book R Markdown: The Definitive Guide

Week 5 – The R language: vectors, classes, functions, iteration (03.05 - 09.05)

• Slides: Vectors, classes, functions, iteration – HTML | PDF
• Screencasts:
  • Vectors
  • Classes
  • Functions
  • Iteration
• Exercise:
  • Ex 5
  • Code-along
• Quiz: Q 4
• Additional material:
  • R4DS chapters:
    • Factors
    • Dates and times
    • Functions
    • Iteration

Week 6 – Linear models (10.05 - 16.05)

• Slides: Linear models - HTML | PDF
• Screencasts:
  • Correlation
  • Linear regression
• Exercise:
  • Ex 6
  • Code-along
• Quiz: Q 5
• Additional material:
  • Tidy Modeling with R chapter: Fitting models with parsnip
  • R4DS chapters:
    • Model basics
    • Model building
    • Many models

Week 7 – Data modeling with tidymodels (17.05 - 23.05)

⚠️ 20.05 – Deadline: project proposal submission & registration ⚠️

• Slides: tidymodels - HTML | PDF
• Screencasts: tidymodels
• Exercise:
  • Ex 7
  • Code-along
• Quiz: Q 6
• Additional material:
  • Tidymodels tutorial
  • Tidy Modeling with R

Week 8 – Creating web applications with shiny (24.05 - 31.05)

• Slides: - HTML | PDF
• Screencasts: shiny
• Exercise: Ex 8
• Quiz: Q 7
• Additional material:
  • RStudio's “Learn Shiny” tutorial. Mastering Shiny
  • Shiny cheat sheet
  • “Awesome” Shiny Extensions

Week 9 – Good practices for programming with R (01.06 - 07.06)

• Slides: Good practices for programming with R - HTML | PDF
• Screencasts: Misc. topics
• Exercise: No exercise this week
• Quiz: No quiz this week
• Additional material: No additional reading this week

Weeks 10+

⚠️ 06.07 – Deadline: project submission ⚠️

⚠️ 09.07 – Deadline: final presentation ⚠️