Data Science Summer School 2023
Knowledge and skills in Data Science are becoming indispensable for researchers of all disciplines. Especially young researchers profit from knowing about the scope and application areas of Data Science in scientific work in specific and across different disciplines. Furthermore, they must understand the belonging implications for scientific inquiries, and the skills required by a data scientist to be productive in a world deluged by data.
The Georg-August-Universität Göttingen is pleased to host an International Summer School on Data Science this year again. For the fourth time since 2017 Master and PhD students are welcome to apply and take part in the Summer School.
Further Information and Application
For details regarding the Summer schoool please have a look at: https://events.gwdg.de/e/DS3-2023
If you are interested to participate we welcome your application via https://events.gwdg.de/e/DS3-2023
THE DATE: September 11-22, 2023
Deadline for applications is 15 May, 2023.
The speakers will give an overview on the multi-layered topics and methods belonging to Data Science. Such as
- Data Quality
- Exploratory and Quantitative Data Analysis
- Deep Learning
- Application examples
- Quantum Machine Learning
- AI Safety and Security
- Scalable AI
Lecturers from several disciplines will enable cross-disciplinary insights. This years summer school opens the opportuinity for the participants to engage with further experts at the HeKKSaGOn AI Symposium wich will take part in Göttingen from September 19-21.
List of Confirmed Speakers
– Harm Alhusen (HAWK): Introduction to AWS SageMaker
– Samy Baladram(Tohoku University): Introduction to Data Science & Timeline Forecasting
– Christian Boehme (GWDG): Quantum Machine Learning
– Benjamin Eltzner (University Göttignen): Exploratory and Quantitative Data Analysis
– Lukas Friedrich (GWDG): Deep Learning
– Georgios Kaklamanos (GWDG): AI Safety & Reproducible Research
– Péter Kíraly (GWDG): Data Quality
– Julian Kunkel (GWDG): Scalable AI & Secure AI
– Faraz Fatemi Moghaddam (Hartmann Group): Security
– Hendrik Nolte (GWDG): Scalable AI & Secure AI
– Constantin Pape (University Göttingen): Introduction to Machine Learning
– Dorothea Sommer (GWDG): Scalable AI & Secure AI
– Ichigaku Takigawa (Kyoto University): Decision Tree Ensemble
In the deep learning part of the course students will:
- learn concepts and techniques underlying deep learning and understand their advantages and disadvantages compared to alternative approaches
- learn to solve practical data science problems using deep learning using the popular PyTorch library
- learn the basics of modern deep learning architectures (convolutional neural networks and transformers) and learn how to implement these architectures in PyTorch
- learn applications of deep neural networks for computer vision and natural language processing tasks
All lectures will be held in English.
Stay tuned for updates on topics and confirmed speakers!
The Summer School will welcome up to 35 participants representing mainly international partner universities of the University of Göttingen. Participants will be granted 3 ETCS for their work during the course.
The prerequisite for an application is a completed Bachelor’s degree programme.
We expect our applicants to have knowledge of the programming language Python as well as basic knowledge in statistics.
Accomodation and travel allowances
For a number of excellent applications we are able to offer free accommodation and a travel allowances.
The Summer School is organised jointly by the Institute of Computer Science, Göttingen International and the GWDG ’s and SUB ’s joint service unit on research data management at the Göttingen Campus, the Göttingen eResearch Alliance .
Responsible organizational Team
- Prof. Dr Ramin Yahyapour (Institute for Computer Science)
- Dr Sven Bingert (GWDG)
- Timo Henne (Göttingen eResearch Alliance, SUB)
- Lena Steilen (GWDG)
This Summer School is supported financially by the University of Göttingen within the HeKKSaGOn network.