Data Science for Business
Course code
SCM461
Course type
BSc Course
Weekly Hours
2,0
ECTS
3,0
Term
FS 2022
Language
Englisch
Lecturers
Prof. Dr. Arne Karsten Strauss
Please note that exchange students obtain a higher number of credits in the BSc-program at WHU than listed here. For further information please contact directly the International Relations Office.
Course content
This course is dedicated to conveying a sense of how to structure analytic projects systematically, from understanding of the business problem over modelling up to model assessment and communication of the project's results (or a project proposal) to a client. The course introduces such a structure with an applied, step-by-step introduction that mixes theory and practical, hands-on implementation tasks (using Tableau and programming in R).
Whilst several fundamental data science techniques are introduced, explained and worked with, we do mainly focus on the overall analytic project process. Ultimately, this will also help to evaluate project pitches from a client’s perspective.
Class dates
| Date | Time |
|---|---|
| Monday, 10.01.2022 | 11:30 - 15:15 |
| Monday, 24.01.2022 | 11:30 - 15:15 |
Learning outcomes
- Ability to structure analytic projects
- Ability to evaluate proposals for analytic projects
- Ability to deliver effective pitches for analytic projects
- Ability to effectively report analytic results to managers
- Ability to design interactive visualizations and dashboards
Literature
F. Provost and T. Fawcett. Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. O’Reilly, 2013
Learningmethods
Lectures interwoven with in-class exercises (students must bring their own laptops).
Exam
Group presentation and report: 40%
Exam: 60%
Requirements
Students unfamiliar with R programming should learn about the basics of R in advance of the module; optional preparation materials will be provided.