After successful completion of the course, students are able to discuss legal and ethical aspects of the use of data, formulate a problem for solving it using Data Science approaches, design rigorous Data Science experiments, and interpret the results of complex data analyses.
The following topics are covered in the lectures:
In addition, two exercises will be done.
The effort breakdown is:
9 2-hour lectures: 18hExercise 1: 10hExercise 2 (incl presentation): 30hExam preparation: 16hExam: 1hSUM: 75h
Lectures, exercises
05.10.2023 14:15-15:45 – Hanbury: Introduction to Course and Data Science12.10.2023 14:15-15:45 – Hanbury: Introduction to Ethical and Legal Aspects19.10.2023 14:15-15:45 – Knees: Data Science Experiments09.11.2023 14:15-15:45 – Knees: Experimental Designs I16.11.2023 14:15-15:45 – Schindler: Hands-on Data Science Workflow23.11.2023 14:15-15:45 – (Backup date - might not be needed)30.11.2023 14:15-15:45 – Knees: Experimental Designs II07.12.2023 14:15-15:45 – Knees: Experimental Designs III14.12.2023 14:15-15:45 – Rauber: Reproducibility21.12.2023 14:15-15:45 – Rauber: Data Management11.01.2024 14:15-15:45 Project Presentations18.01.2024 14:15-15:45 Project Presentations25.01.2024 14:15-15:45 Project Presentations25.01.2024 18:00-20:00 Written ExamMarch 2024 Exam repeat 1May 2024 Exam repeat 2
2 Exercises, Exam