DATA SCIENCE TOOLBOX
02.06.2023 – 23.06.2023

This certificate course introduces participants to the world of data science and the handling and use of data. In an increasingly data-driven world, organisations have access to a wealth of data that can be used to make better make better decisions and develop innovative solutions. Data Science enables us to understand, process and analyse this data, to gain useful insights and make predictions. This course is explicitly not only about the analysis of given data, but also about the planning of data science projects from the ground up and therefore addresses different methods for obtaining data. Theoretical content in the course is always accompanied by hands-on applications in R. In addition, some useful web services are included.

Learning goals

The course teaches a wide range of data analysis and visualisation techniques. Participants learn different machine learning techniques and understand how to apply statistical models and analyse data in an exploratory way. After successful completion of the course, participants will be able to apply the taught methods along the information life cycle and thus implement their own data-based research projects. The course includes different approaches of data collection, data analysis up to techniques of data visualisation. In addition, the course teaches basic and applied statistical and programming skills.

Content

Web scraping
Experiment design and implementation
Basics of data processing in R
Regression analysis and interaction effects
Network analysis
Machine learning
Data visualisation

The content is supplemented and tested using case studies and real data examples.

Target group

The course is aimed at university graduates from all fields of study.

Prerequisites

In-depth interest in Data Science
Laptop/PC + headset with microphone

Dates

Virtual classroom sessions will take place on the following days:

June 02, 2023, 09:00-15:00 (CET)
June 09, 2023, 09:00-15:00 (CET)
June 16, 2023, 09:00-15:00 (CET)
June 23, 2023, 09:00-15:00 (CET)

The first virtual classroom sessions will be followed by a period of self-study. This will be accompanied by the lecturer for 4 hours on each of the following Saturdays: June 03, 2023; June 10, 2023; June 17, 2023; June 24, 2023.

LECTURER

Prof. Dr. Timm Teubner

Prof. Dr. Timm Teubner researches as a Professor at the Einstein Center Digital Future (ECDF) and Technische Universität Berlin the topic "How does trust emerge online?" from an economic, technical, and sociological perspective. His research interests include online platforms and multi-sided markets, reputation systems, internet auctions, user behavior, sharing and crowd-X approaches, and cybersecurity. He studied industrial engineering at the Karlsruhe Institute of Technology from 2004 to 2010, where he also earned his doctorate and subsequently took on a postdoctoral position. During his studies, he spent a year at the University of Massachusetts (UMass) in the USA. His research is interdisciplinary and finds application in a variety of digital platforms - from the A’s of Amazon/Airbnb; to the B’s of BlaBlaCar/Booking; and the C’s of Clickworker/Craigslist,... to the Z’s of Zimride/Zalando. Prof. Dr. Teubner finds inspiration for his research at the piano and during (ultra) marathons. His research has been published in numerous renowned international journals and conference proceedings.

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