Data Science in Practice
MBA TECH -- Faculty of Management
Last Updated: 2026-09-28
Goal
The goal of this module is to show data science in practice. We use real data, tranform it so it can be used for modelling, build different models and show how the best model can be selected. The journey continues by investigating how bias, prior assumptions, and modelling choices affect fairness of the model.
We focus on a selection of the material presented in the boook "The big R-book: from data science to learning machines and big data." We use it to build a solid model given a dataset, verify models and ponder ethical dillemas.
The homepage of the book is here.
Calendar
| # | Date | Time | Where | Content |
|---|---|---|---|---|
| 1 | 2027-01-30 | 8:30–12:30 | TBD | Data Science in Practice |
The Course Book
Do you prefer to print the course materials? Download the printable version of the that contains all lectures in one handy book. There is no need to print all separate materials.
Lectures and Content
| # | Lecture | Description | Downloads | Other Resources |
|---|---|---|---|---|
| 1 | Ethics in AI and Financial Services | An introduction to Ethics. What is it? What is ethical and what not? How does the reference point of view our judgement? | . | |
| 2 | Bias in data | Recognising bias in data and models and building robust, unbiased models. | ||
| 3 | Case Study | Building a model for car insurance acceptance, cross validation and selecting a model. |