09.11.2023 - 10.11.2023 + 16.11.2023
Certificate of Participation
Prof. Dr. Timm Teubner
DATA SCIENCE TOOLBOX
09.11.2023 – 10.11.2023 + 16.11.2023
This 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 goalsThe 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.
- Web scraping
- Experiment design and implementation
- Basics of data processing in R
- Regression analysis and interaction effects
- Network analysis
- Machine learning
- Data visualisation
Target groupThe course is aimed at university graduates from all fields of study.
- In-depth interest in Data Science
- Laptop/PC + headset with microphone
DatesNovember 09 - 10, 2023 and November 16, 2023 (virtual classroom sessions).
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.