Course material

The complete course material

Session Date Topic Slides
1 March 17, 2022 General introduction Slides Orga, Slides Install
2 March 23, 2022 Philosophy of Data Science Slides Philo
3 March 24, 2022 First steps in R Slides
4 March 31, 2022 Basic object types Slides
5 April 6, 2022 Advanced object types Slides
6 April 7, 2022 Visualization I Slides
7 April 27, 2022 Projects and data import Slides
8 April 28 and May 4, 2022 Data wrangling I Slides
10 May 5, 2022 R Markdown Slides
11 May 12, 2022 Intro models Slides
12 May 18 and May 19, 2022 Simple Linear Regression Slides
14 June 1 and June 2, 2022 Multiple Linear Regression Slides
16 June 9, 16 and 23, 2022 Sampling Theory Slides
A1 Omitted Bootstrap and confidence intervals Slides
A2 Omitted Hypothesis testing Slides

Session 1: Introduction and installation

Mandatory readings

Session 2: Philosophy of Data Science

Mandatory readings

Session 3: First steps in R I - Basics and functions

Mandatory readings

Further readings

Exercises

After installing (and updating) the DataScienceExercises-package (as described here), run the following command from within your R session:

learnr::run_tutorial(
  name = "Basics", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

Session 4: Basic object types

Mandatory readings

Exercises

learnr::run_tutorial(
  name = "ObjectTypes1", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

Session 5: Advanced object types

Mandatory readings

Exercises

learnr::run_tutorial(
  name = "ObjectTypes2", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

Session 6: Visualization

Mandatory readings

Further readings

Exercises

learnr::run_tutorial(
  name = "Visualization1", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

Session 7: Project organization and data import

Mandatory readings

Exercises

learnr::run_tutorial(
  name = "ProjectOrga", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

Sessions 8 & 9: Data wrangling

Mandatory readings

Further readings

Exercises

learnr::run_tutorial(
  name = "Wrangling1", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

Session 10: R Markdown

Mandatory readings

Further reading

Exercises

learnr::run_tutorial(
  name = "RMarkdown", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

The practical exercise for this topic can be found here.

Session 11: Modelling data

After installing (and updating) the DataScienceExercises-package (as described here), run the following command from within your R session:

Exercises

After installing (and updating) the DataScienceExercises-package (as described here), run the following command from within your R session:

learnr::run_tutorial(
  name = "Models", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

Sessions 12 & 13: Simple linear regression

Mandatory readings

Exercises

learnr::run_tutorial(
  name = "LinearRegression1", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

Sessions 14 & 15: Multiple linear regression

Mandatory readings

Exercises

learnr::run_tutorial(
  name = "LinearRegression2", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

Sessions 16 & 17: Sampling theory

Mandatory readings

Exercises

learnr::run_tutorial(
  name = "Sampling", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

Session A1: Bootstrapping and confidence intervals (omitted)

Mandatory readings

Session A2: Hypothesis testing (omitted)

Mandatory readings