Online Course Guide of WHU –

Find all modules and courses of our degree programs.

Please use the filters below to select the term (spring or fall) as well as the respective program (BSc, MSc, MBA, Exchange, Doctoral) of your choice for an overview of all modules offered at WHU. The courses are listed under the modules. Please click on a module to see which courses are part of it. If you would like to find out more about a certain course, click on the name of the course to see detail information. The location of the lecture will be revealed after your course registration on myWHUstudies.

Spring term counts from January - August, fall term counts from September - December.

Important for Exchange Students: As the Full-Time and Part-Time MBA Programs utilize a modular course structure, the dates on which students begin and end the exchange are flexible. Please find here a chronological overview of the preliminary course offering for Fall and Spring.

Spring 2021  ›  Bachelor of Science  ›  Bachelor of Science - 4th Semester  ›  Data Science for Business and Pricing Analytics

Data Science for Business

Course Code:
SCM461
Lecturers:
Prof. Dr. Arne Karsten Strauss, Jan-Rasmus Künnen
Course Type:
BSc Course
Week Hours:
2,0
Term:
Spring 2021
Language:
Englisch
Credits:
3,0
(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.)
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.

Date
Time
08:00 AM till 11:15 AM
Tuesday, 19/01/2021
08:00 AM till 11:15 AM
Wednesday, 17/02/2021
08:00 AM till 11:15 AM
Monday, 26/04/2021
02:00 PM till 05:00 PM
  • 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
F. Provost and T. Fawcett. Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. O’Reilly, 2013
Lectures interwoven with in-class exercises (students must bring their own laptops).
Group presentation and report: 40%

Exam: 60%

Students unfamiliar with R programming should learn about the basics of R in advance of the module; optional preparation materials will be provided.
90