Marcel Steffen M.Sc.

Wissenschaftlicher Mitarbeiter

Telefon: +49 40 42878 - 4191 | Fax: +49 40 42731 - 4198
E-Mail: marcel.steffen@tuhh.de

Technische Universität Hamburg, Institut für Verkehrsplanung und Logistik W8
Am Schwarzenberg-Campus 3, D-21073 Hamburg | Gebäude E, Raum 1.073

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Lehre


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Building Business Data Products (PBL)
Untertitel:
This course is part of the module: Business & Management
DozentIn:
Prof. Dr. Christoph Ihl, Joschka Schwarz
Semester:
SoSe 24
Ort:
nicht angegeben
Zeiten:
Termine am Montag, 01.07.2024 - Mittwoch, 03.07.2024 10:00 - 18:00
Erster Termin:Montag, 01.07.2024 10:00 - 18:00
Leistungsnachweis:
tm2546 - Building Business Data Products (subject theoretical and practical work)<ul><li>p1599 - Building Business Data Products: Subject theoretical and practical work</li></ul>
Leistungspunkte:
2
Beschreibung:

Building Business Data Products is a project based course designed to provide you with a sound understanding of the constantly growing opportunities that business analytics experiences through modern approaches in data science and machine learning. In this course you will learn methods of descriptive, predictive and prescriptive analytics in order to approach critical business decisions based on data and to derive recommendations for action. Participants learn how to collect, cleanse and transform large amounts of data using various techniques. The aim is to specifically examine, visualize and model the associated data using modern machine learning methods.

During the course, the participants apply the tools they have learned to practical data science problems from various management areas, creating a comprehensive and multifaceted application portfolio that demonstrates their data analysis and modeling skills. The programming language used is R, whereby the integration of Python into the workflow is also practiced. Programming knowledge is not required, but is of course an advantage. Each session will involve a small amount of lecturing on R concepts, and a large amount of time for students to complete assigned coding and analysis problems.

Learning objectives:

After completing this module, students will be able to:

• Execute a complex data science project

• Communicate the results in an actionable form of products, dashboards and applications  with RMarkdown, Shiny, Flexdashboard