Semester:WS 16/17
Art:Modul/LV/Prüfung
Sprache:Englisch
ECTS-Credits:6.0
Plansemester:3
Lektionen / Semester:58.0 L / 43.5 h
Selbststudium:136.5 h
Art:Modul/LV/Prüfung
Sprache:Englisch
ECTS-Credits:6.0
Plansemester:3
Lektionen / Semester:58.0 L / 43.5 h
Selbststudium:136.5 h
Modulleitung/Dozierende
- Prof. Dr. Markus Weinmann
(Modulleitung)
- Dr. Nadine Székely
(Modulleitungsassistenz)
Studiengang
Masterstudium Information Systems (01.09.2015)Lehrveranstaltungen
Beschreibung
Short description
In this course, students apply acquired data science knowledge and skills to solve a real-world business problem from the area of marketing, finance, or operations.
Topics may include
- Supervised learning (regression, classification)
- Unsupervised learning
- Text mining
- Social network analysis
- Assessing model quality
Learning objectives
- Students will analyze a real-world case through the data science lens
- Students will collect and prepare data for later analysis
- Students will build and evaluate statistical models
- Students will translate statistical models into actionable results
Methods
- The module integrates theoretical knowledge and practical skills in a seminar focusing on a real-world case.
- The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.
Kompetenzen
Prüfungen
- PWW-MA_Project Seminar Data Science (WS 16/17, bewertet)