Extend your skills and competences by finding the right learning path for your needs in this extensive course portfolio! The platforms of the Information & Data Science Framework have developed a coordinated course offer that covers a wide array of topics.
The five Helmholtz Information & Data Science Platforms - Helmholtz AI, Helmholtz Imaging, HIDA, HIFIS, HMC - offer a comprehensive portfolio of courses, covering topics from introductory programming to advanced statistical modeling and AI techniques.
What makes our training portfolio unique is the applied approach that is predominant in all our courses. Practical applications and case studies are designed to prepare you to succeed in your research or project.
Discover our diverse clusters for data scientists
The courses are structured into five thematic clusters, reflecting key areas of Information and Data Science. They provide orientation within a diverse training portfolio and support the targeted development of relevant competencies.
Courses can be selected and combined flexibly according to individual interests and needs as well as prior knowledge. Courses that do not require prior knowledge are specifically highlighted, offering an accessible entry point into the field.
Programming
Programming
Build solid programming skills for data-driven research. Learn to systematically translate scientific questions into code, process data efficiently, automate analyses, and develop transparent, reproducible workflows—with courses in MATLAB, Python, and R.
The following courses are available to you free of charge!
Beginner:
Kickstart R
Introduction to R
Kickstart Python
First Steps in Python
Intermediate:
RMarkdown
Graphics with R
Data Processing with Pandas and Visualization with Matplotlib
Object-Oriented Programming
Statistics
Statistics
Deepen your understanding of probability theory, hypothesis testing, regression, and more. This cluster is ideal for learners who want to ground their data science practice in statistical methods.
The following courses are available to you free of charge!
Beginner:
Intermediate:
Tools and Practices in Programming
Tools and Practices in Programming
This topic cluster focuses on practical tools and workflows that are used daily in software development. You will learn how to version code, automate processes, publish results, and visualize data in a clear and understandable way.
The following courses are available to you free of charge!
Beginner:
Kickstart Shell & Git
Introduction to Git & GitLab
Foundations of Research Software Publication
Intermediate:
Continuous Integration
Principles of Data Visualization
FAIR and Data Management
FAIR and Data Management
This topic cluster shows how to prepare and document research data so that it remains usable in the long term. You will learn how to use metadata effectively and apply the FAIR principles in practice to increase the reusability of your data.
The following courses are available to you free of charge:
Beginner:
Metadata Management: From Key Essentials to Practice
Reusability of Scientific Data for Matter
Fundamentals of Scientific Metadata for Health
AI and Data Science
AI and Data Science
With machine learning and deep learning as foundational pillars, the courses in this cluster prepare learners for advanced AI tools and applications. Courses ranging from Explainable AI to supercomputers, dimensionality reduction, uncertainty quantification, and AI-based imaging techniques define the learning path in this cluster.
The following courses are available to you free of charge:
Beginner:
Six Main Tasks in Image Processing
3D Data Visualization
Introduction to Image Registration
Intermediate:
Basic Methods in Machine Learning / Introduction to Machine Learning
Introduction to Large-Language Models for Science
Introduction to Deep Learning
Kickstart Deep Learning
Understanding Transformers
Regularization in Image Reconstruction
Image Dataset Quality Control, Data Exploration, and PixelPatrol
Advanced:
Introduction to Simulation-Based Inference
Validating AI for Image Analysis
Introduction to Uncertainty Quantification
Advanced Methods of Machine Learning
A Practical Guide to Dimensionality Reduction
Introduction to Explainable AI
Information and Data Science Framework
Information and Data Science Framework
The course portfolio is part of a joint, cross-platform initiative of the Helmholtz Information & Data Science platforms and is designed to support researchers across different career stages as well as all other interested Helmholtz staff.
The platforms are one of the initiatives of the Helmholtz Information & Data Science Framework.
Take the first step on your learning path to increase your data science expertise and succeed with your project. Do you have any questions or feedback? Please do not hesitate to contact us!
Contact
Dr. Stephanie Schworm
Training Program Manager
Contact
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