Semester:WS 18/19
Type:Module/Course/Examination
Language:English
ECTS-Credits:6.0
Scheduled in semester:3
Semester Hours per Week / Contact Hours:58.0 L / 43.5 h
Self-directed study time:136.5 h
Type:Module/Course/Examination
Language:English
ECTS-Credits:6.0
Scheduled in semester:3
Semester Hours per Week / Contact Hours:58.0 L / 43.5 h
Self-directed study time:136.5 h
Module coordination/Lecturers
- Ass.-Prof. Dr. Johannes Schneider
(Modulleitung)
- Marcus Basalla, M.Sc.
(Modulleitungsassistenz)
Curricula
Master's degree programme in Information Systems (01.09.2015)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 learningText mining
- Social network analysis
- Assessing model quality
- Assessing technologies
Learning Outcomes
- 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
- Student will work together as a team
Qualifications
Lectures Method
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.
Exam Modalities
An attendance of min. 80% is necessary to obtain a positive grade in this course.
A final report and two presentations will be graded.
Exams
- PWW-MA_Project Seminar Data Science (WS 18/19, bewertet)