*Schedule may be subject to change closer to the course

Monday 2021-10-04

09:00 - 10:00 Welcome (Olga, Eva)

10.00 - 10:45 Introductory lecture (Bengt)

11.00 - 12:00 Mathematical foundations (Olga)

12:00 - 13:00 lunch (offline)

13:00 - 13.30 Descriptive statistics (Eva)

13.30 - 14.30 Exercises: descriptive statistics

14.30 - 15.00 break (offline)

15:00 - 15:30 Probability: introduction and discrete distributions (Eva)

15.30 - 16.30 Exercises: probability & discrete distributions

16.30 - 17.00 Daily challenge

Tuesday 2021-10-05

09:00 - 09:45 Group discussions: recap of the previous day

09:45 - 10:15 Probability: continuous distributions (Eva)

10:15 - 11:00 Exercises: cont. random variable and Exercises: random sample

11:00 - 11:30 Statistical inference: Hypothesis tests using resampling (Eva)

11:30 - 12:00 Exercises: hypothesis tests

12:00 - 13:00 lunch (offline)

13:00 - 13:30 Statistical inference: Parametric tests (Eva)

13:30 - 14:30 Exercises: parameteric tests

14:30 - 15:00 break (offline)

15:00 - 15:30 Statistical inference: Point and interval estimates (Eva)

15:30 - 16:30 Exercises: interval estimates

16:30 - 17:00 Daily challenge

Wednesday 2021-10-06

09:00 - 09:45 Group discussions: recap of the previous day

09:45 - 11:00 Linear models: introduction (Olga)

11:00 - 12:00 Exercises: linear models introduction

12:00 - 13:00 lunch (offline)

13:00 - 14:00 Model coefficients & model diagnostics

14:00 - 14:30 Exercises: model coefficients

14:30 - 15:00 break (offline)

14:30 - 15:30 Exercises: model diagnostics

15:30 - 16:00 Generalised Linear Models

16:30 - 17:00 Daily challenge

Thursday 2021-10-07

09:00 - 09:45 Group discussions: recap of the previous day

09.45 - 12:00 Principal Component Analysis (Payam)

12:00 - 13:00 lunch (offline)

13:00 - 13:30 Clustering: k-means and hierarchical clustering (Eva)

13:30 - 14:30 Exercises: clustering

14:30 - 15:00 break (offline)

15:00 - 15:30 Introduction to supervised learning: classification and regression (Olga)

15:30 - 16:30 Exercises: introduction to supervised learning

16:30 - 17:00 Daily challenge

Friday 2021-10-08

09:00 - 09.45 Group discussions: recap of the previous day

09.45 - 10:30 Feature selection & model evaluation (Bengt)

10.30 - 12:00 Exercises: feature selection

12:00 - 13:00 lunch (offline)

13:00 - 14:00 Random Forest (Payam)

14:15 - 15:00 Exercises: random forest

15:00 - 16:00 Course wrap-up

anytime after 15.00 Daily challenge

anytime after 15.00 Feedback survey