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Applied Data Thinking

Kurs ID
GEN433
Art des Kurses
BSc Kurs Studium Generale
Wochenstunden
2,0
ECTS
3,0
Semester
HS 2020
Vortragssprache
Englisch
Vortragende/r
Marc Weimer-Hablitzel
Bitte beachten Sie, dass AustauschstudentInnen im BSc-Programm der WHU eine höhere Anzahl an Credits erwerben als hier aufgeführt. Für weitere Informationen wenden Sie sich bitte direkt an das [International Relations Office].
Fall Term 2020: The course will be held online.

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

Date Time
Thursday, 29.10.2020 15:30 - 18:45
Friday, 30.10.2020 08:00 - 11:15
Thursday, 12.11.2020 15:30 - 18:45
Friday, 13.11.2020 08:00 - 11:15
Thursday, 19.11.2020 15:30 - 18:45
Friday, 20.11.2020 08:00 - 11:15
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 course work will include case studies evaluating data, writing code and making business decisions using the results. The goal of the course is not to train you as a Data Scientist but to be able to read and evaluate analytic approaches and products from reading code to evaluating potential machine-learning use cases. The course will introduce the programming language Python. You do not need any prior knowledge in Python Programming.

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
90
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