Online Course Guide of WHU –

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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.

Fall 2022  ›  Bachelor of Science in International Business Administration  ›  5th Semester  ›  Studium Generale

Applied Data Thinking

Course Code:
Marc Weimer-Hablitzel
Course Type:
BSc Course General Studies
Week Hours:
Fall 2022
(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.)
Each Block will be covered in 2 Sessions, which will take place on two consecutive days:

Elementary Concepts of Data Thinking and Analysis

Data Gap Analysis using Machine-learning techniques

Introduction to Python Programming of a simple machine learning algorithm

Thursday, 10/11/2022
03:30 PM till 06:45 PM
Friday, 11/11/2022
08:00 AM till 09:30 AM
Thursday, 17/11/2022
03:30 PM till 05:00 PM
Friday, 18/11/2022
08:00 AM till 09:30 AM
Text chapters and cases will be posted on the online course website before the beginning of the course. All PowerPoints used in this course will be made available to students shortly after class.
The goal of the course is to get to know data thinking as an innovation method. It is about analyzing business potentials, implementing the findings and understanding how an expert data scientist approaches data problems. Therefore, you can appreciate the AI and ask the right questions to understand a data scientist's technique well. Moreover, you will use machine learning on explicit examples by small coding challenges with Python. Basic knowledge of Python Programming is not required to attend this course.You will learn all the needed skills there.

Sessions will consist of lectures, discussion and and case work. There will also be a group project due for hand-in and presentation (presentation is on the last class day). Case work and project specifications will be explained, and groups will be assigned, at the beginning of the course.
The course will be either pass or fail.

70% Class participation, in-class assignments and homework

30% Online Course Quizzes

This course will introduce students to methods for data driven decision-making in business. It will cover methods designed to provide evidence for two types of fundamental business issues. The first is identifying data use-cases and the second is evaluating and validating possible solutions. The course is intended to train business leaders to