Applied Data Science

B.A. International Management — Fall Semester 2026/27

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Affiliation

📑 The course in brief

Focus: Turning raw data into decisions you can defend. You learn to import, clean, visualize and model real business data with R, and to communicate what you found in a reproducible report that anyone can re-run and check.

How: Twelve Monday sessions, 09:00–11:15, room MAD 099. Every session mixes a short input lecture, a live coding demo where you follow my coding and ask questions, and hands-on work on real business data — with time to discuss what came out of it.

Prerequisites: Research Methods / Statistik I and II. We build on what you already know and deliberately do not repeat it. You need a laptop you can install software on and bring to every session.

🎯 Learning Objectives

By the end of the course you will be able to:

Write R code to import, clean and reshape messy business data
Produce reproducible reports with Quarto, in HTML and PDF
Track and share your work using Git and GitHub
Build visualizations that answer a question — and spot the ones that mislead
Predict an outcome, and know how wrong you are likely to be
Tell supervised from unsupervised machine learning, and use one of each
Use free AI assistants productively — and check their output critically

📋 Assessment

Three Quarto reports during the semester — written individually, graded pass/fail, with one revision in total; all three must be passed to sit the exam
Final exam — 120 minutes, open book, written on your own laptop and handed in through Classroom 50; free AI assistants are allowed

The Seminar Description has the full schedule, an overview of every session and all the details on assessment. Deadlines and the submission rules are on the Reports page. The task sheets come with each report: on Moodle for Report 1, in your Classroom 50 repository for Reports 2 and 3. Practical matters — what to install, where things happen — are on Getting Started.