Data Science Services
Funding proposals
- Reviewing data science parts in your proposals
Data Science Pipeline
- Analysing your research questions from data science perspective Helping to get data (APIs, web scraping, databases, files)
- Scrubbing and cleaning your data (Python, R)
- Exploratory data analysis (Python, R)
- Modelling your data (training neural networks) (Python, R)
- Data visualization and storytelling (Python, R)
- Consulting on publishing a data paper in a data journal FAIR Sharing and archiving your data, models and visualizations in data repositories
Codes and algorithms
- Writing a reproducible open-source code (Python, R)
- Code organization and documentation at GitHub
- Reviewing your software repo FAIR sharing and archiving your software in data repositories
- Consulting on publishing a software paper in a software journal
Infrastructure for data science
- Consulting on computational resources, high performance computing (HPC)
- Consulting on free cloud infrastructure and programs (Kaggle, Google Colab, Google Cloud for education, TPU Research Cloud)
- Consulting on deploying deep learning models in production
Low-code and no-code data science
- Consulting on low-code libraries (PyCaret, H20 AutoML, Auto-ViML, TPOT, AutoKeras)
- Consulting on no-code tools (Google Cloud Auto ML and ML KIT, Runway AI, Lobe, CreateML, RapidMiner, DataRobot)
- Consulting on researching with chat bots (ChatGPT and its alternatives)
Networking
- Helping to search cooperation partners
- Helping in organizing data science meetups
- the Mannheim Center for Data Science
Contact
Forschungsdatenzentrum (FDZ)
Team: Irene Schumm, Phil Kolbe, David Morgan, Thomas Schmidt, Renat Shigapov, Christos Sidiropoulos, Vasilka Stoilova, Larissa Will
University of Mannheim
Universitätsbibliothek Mannheim
Schloss Schneckenhof West
68161 Mannheim
Universitätsbibliothek Mannheim
Schloss Schneckenhof West
68161 Mannheim
