Course Schedule

Dates and Times (All Lectures and labs will be Digital via Microsoft Teams)


Course week Tuesday (11:00 - 12:45) Thursday (time labgroup dependent)
Week 1 27 April: no class 29 April: lab 1
(Kingsday)
Week 2 4 May: Lecture week 2 6 May: lab 2
Week 3 11 May: Lecture week 3 13 May: no class (ascension day)
Week 4 18 May: Lecture week 4 20 May: lab 4
Week 5 25 May: Lecture week 5 27 May: lab 5
Hand in assingment 1
Week 6 1 June: Lecture week 6 3 June: lab 6
Week 7 8 June: Lecture week 7 10 June: lab 7
Week 8 15 June: Lecture week 8 17 June: lab 8
Week 9 22 June: Lecture week 9 24 June: lab 9
Hand in assignment 2
Week 10 29 June: no class 1 July: 15:15 - 18:45 digital EXAM

Topic overview

Week Topic Required Reading
Week 1 Introduction to the course The Syllabus; ISL Chapter 1 & 2.1
Week 2 Visualizing data - exploratory data analysis DATVIS Chapter 1, 4 & 5 (section 5.3 & 5.4)
Week 3 Model accuracy and model fit ISL Chapter 2.2 & 5.1
Week 4 Linear regression for data science ISL Chapter 3.1-3.4, 6.1-6.2
Week 5 Classification ISL Chapter 4
Week 6 Moving beyond linearity ISL Chapter 7
Week 7 Visualizing data - interactive data visualization Mastering Shiny Chapter 2 - 5
Week 8 Tree based methods ISL Chapter 8
Week 9 Text mining TMwR Chapters 1, 2 & 3
Week 10 Exam week!