Applied Data Thinking
Course code
GEN433
Course type
BSc Course General Studies
Weekly Hours
2,0
ECTS
3,0
Term
HS 2021
Language
Englisch
Lecturers
Marc Weimer-Hablitzel
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
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
Class dates
| Date | Time |
|---|---|
| Thursday, 28.10.2021 | 15:30 - 18:45 |
| Friday, 29.10.2021 | 08:00 - 11:15 |
| Thursday, 11.11.2021 | 15:30 - 18:45 |
| Friday, 12.11.2021 | 08:00 - 11:15 |
| Thursday, 18.11.2021 | 15:30 - 18:45 |
| Friday, 19.11.2021 | 08:00 - 11:15 |
| Wednesday, 24.11.2021 | 15:30 - 18:45 |
| Friday, 26.11.2021 | 08:00 - 11:15 |
Literature
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.
Learningmethods
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.
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.
Exam
The course will be either pass or fail.
70% Class participation, in-class assignments and homework
30% Online Course Quizzes
Requirements
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