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 six 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 with R
Programming with R
Harness the power of R. Learn how to code with R, learning to read, manipulate, and visualize data while building reproducible workflows and manuscripts tailored for scientific research.
Kickstart Shell & Git
Introduction to Git & GitLab
Foundations of Research Software Publication
Continuous Integration
Fundamentals of Software Testing
Statistics
Statistics
Deepen your understanding of probability, hypothesis testing, regression, and more. This cluster is perfect for learners aiming to ground their data science practice in rigorous statistical methods.
Open Research
Open Research
Unlock the potential of open science through courses on collaborative research practices and project management, open-source tools and software, and publishing ethically sound, reproducible, and transparent results.
Kickstart Shell & Git
Introduction to Git & GitLab
Foundations of Research Software Publication
Continuous Integration
Fundamentals of Software Testing
Python Fundamentals
Python Fundamentals
Start with the building blocks of Python, the groundwork for AI based techniques like machine learning. These courses guide you through core programming concepts and the development of reusable, efficient code.
First Steps in Python
Data Processing with Pandas & Data Visualization with Matplotlib
Kickstart Python
Object Oriented Programming
AI and Data Science
AI and Data Science
With machine learning and deep learning being the cornerstones, the courses in this cluster prepare the learners for advanced AI tools and applications. Courses from explainable AI to supercomputers, dimensionality reduction, uncertainty quantification, and AI based imaging techniques mark the learning journey in this cluster.
Basic Methods in Machine Learning / Introduction to Machine Learning
Understanding Transformers
Advanced Methods in Machine Learning
Introduction to Uncertainty Quantification
Introduction to Deep Learning
A Practical Guide to Dimensionality Reduction
Introduction to Explainable AI
3D Data Visualization
Regularization in Image Reconstruction
Six Main Tasks in Image Processing
Validating AI for Image Analysis
FAIR and Data Management
FAIR and Data Management
Master the principles of good research data management. Explore topics like FAIR (Findable, Accessible, Interoperable, and Reusable) and metadata tools to ensure your analyses are both impactful and responsible.
Metadata Management: From Key Essentials to Practice
Fundamentals of Scientific Metadata for Health
Reusability of Scientific Data - Matter
Metadata for Scientific Data Integrity: A 5 Step Training
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.
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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!
Dr. Stephanie Schworm
Training Program Manager
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