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Modern Tools and Applications of Data Science

Course code
QUANT509
Course type
MSc Course
Weekly Hours
2,5
ECTS
5
Term
HS 2021
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.

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 programming in R). The course also comprises an introduction to visualisation techniques and creation of interative charts, maps and dashboards with Tableau.

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
Thursday, 28.10.2021 08:00 - 11:15
Tuesday, 02.11.2021 15:30 - 18:45
Thursday, 11.11.2021 11:30 - 15:15
Tuesday, 16.11.2021 15:30 - 18:45
Tuesday, 23.11.2021 08:00 - 11:15
Thursday, 02.12.2021 11:30 - 15:15
Monday, 06.12.2021 11:30 - 15:15
Tuesday, 07.12.2021 09:45 - 11:15
Wednesday, 15.12.2021 09:00 - 10:30
  • 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).
Weekly individual assignments based on real-life case study, assessed via Moodle quizzes: 15%

Group presentation: 25%

Exam: 60%

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