|
Title
|
|
HIDA Annual Conference
|
|
Data Science & Health: "Next-generation biomedical image analysis competitions"
|
|
HIDA Lectures @ HEIBRiDS
|
|
Programming with R
|
|
German Reproducibility Day
|
|
Data Science Colloquium: Machine Learning for X-Ray and cryo EM at SLAC
|
|
HIP Winter School 2021
|
|
AI-Hero Hackathon on Energy Efficient AI
|
|
Data Science Seminar: Statistical Recovery of Compositional Discrete Structures
|
|
7th International Autumn School on AI and Big Data
|
|
ML@Hereon 35: A Rare Case of Medium Range Weather Forecasting Well Done with Resnets
|
|
2. Helmholtz Open Science Forum: Helmholtz in der Nationalen Forschungsdateninfrastruktur (NFDI)
|
|
First steps in Python-Programming
|
|
Python from 0 to Data Analysis for KIT
|
|
Introduction to Supercomputing at JSC - Theory & Practice
|
|
HIDA Lectures@HEIBRiDS: The Data Donation Project - How wearable sensors can help in dealing with the COVID-19 crisis
|
|
HIDA Lectures@HDS-LEE: Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics
|
|
MarDATA Online Lecture Series: "Marine Data Visualization: Ocean Data View"
|
|
61th Online Seminar: Open Access Publishing – Zooming in on Copyright and CC Licenses
|
|
ELLIS Life/NCT Data Science Seminar: Machine Learning for Single Cell Omics
|
|
CfA: campusSOURCE Award 2022
|
|
TEACH - Talk about Education Across Communities in Helmholtz
|
|
ORCID DE Online-Seminar "Persistent Identifier in Publikations- und Affiliationsrichtlinien"
|
|
Data Science Colloquium | Prof. Kutyniok | “Deep Learning meets Shearlets: Explainable Hybrid Solvers for Inverse Problems in Imaging Science"
|
|
ML@Hereon episode 35: "One column, many steps"
|
|
Women in Data Science: Prof Julia Schnabel
|
|
Helmholtz Open Science Praxisforum Forschungsdatenmanagement
|
|
Applying Data Science
|
|
Programming with Python
|
|
Programming with R
|
|
GitLab for Software Development in Teams
|
|
Project Management with GitLab (Cancelled)
|
|
Test Automation with Python (Rescheduled)
|
|
ML@HZDR Symposium 2021
|
|
CASUS Annual Workshop 2021 - "Digital Twins of Complex Systems"
|
|
62. Helmholtz Open Science Online-Seminar: Die IPCC FAIR Datenrichtlinien aus der Sicht des IPCC Data Distribution Centres (DDC)
|
|
Einführung in Python
|
|
Data Science Colloquium | Prof. Gohlke | “Enzyme function - much to understand, optimize, and discover"
|
|
Introduction to Scalable Deep Learning
|
|
Helmholtz GPU Hackathon 2022
|
|
6. ORCID DE: ORCID in erweiterten Kontexten – Ergebnisse und Ausblick von persistenten Identifiern in Wissenschaft und Kultur
|
|
Version Control with Git
|
|
Artificial Intelligence in Digital Health (AIDHeal)
|
|
Data Science & Health: "Trends and Topics in Text Analytics"
|
|
Data Science & Health: "Combinatorial Optimization Techniques for Bioimaging"
|
|
Data Science & Health: "Machine Learning for Genomics"
|
|
Data Science & Health: "Introduction to Visual Data Science"
|
|
Foundations of Research Software Publication
|
|
Test Automation with Python
|
|
Test Automation with Python
|
|
GitLab for Software Development in Teams
|
|
Introduction to Git and GitLab
|
|
Helmholtz AI special edition seminar - Joris van Eijnatten
|
|
Information Event on HIDA Researcher Grants
|
|
Introduction to Shell + Git + GitLab
|
|
First Steps in Python
|
|
Software Carpentry (Shell, Git, R for Reproducible Scientific Analysis)
|
|
Data Science Colloquium | Prof. Noé | “Deep Learning for Molecular Physics"
|
|
HIDA Lecture @ HIDSS4Health
|
|
Introduction to parallel programming with MPI and OpenMP
|
|
Data Carpentry: Genomics
|
|
ML@Hereon Episode 39: "Extreme Events, Modest Models"
|
|
63rd Helmholtz Open Science Online Seminar
|
|
Introduction to R & Statistical Models with R
|
|
Infosession for Helmholtz Scientists - Become a Host for the HIDA Research Grants
|
|
RDA Deutschland Tagung 2022
|
|
Data Science Jobs for Health @ Helmholtz
|
|
Graphics with R
|
|
ML@Hereon Episode 40: "Foiled Again?"
|
|
DLR OpenSearch Colloquium: Information Extraction and Entity Linking for Semantic Web Search
|
|
2. Helmholtz Open Science Forum: Forschungssoftware
|
|
Science Communication - Write Your Own Blog
|
|
Introduction to Shell + Git + GitLab
|
|
ML@Hereon Episode 41: "Futureproof your training data"
|
|
Data Carpentry: Ecology with Python
|
|
Reproducibility for Matter Research - Reproducibility in Research by R4E
|
|
Reproducibility for Matter Research - Foundation of Research Software Publication
|
|
Introduction to Statistics
|
|
Mixed Models
|
|
64th Online Seminar: OpenAlex
|
|
RMarkdown
|
|
Multivariate Statistics
|
|
Introduction to R
|
|
Graphics with R
|
|
Introduction to Statistics
|
|
Multivariate Statistics
|
|
RMarkdown
|
|
Helmholtz AI Virtual Roadshow
|
|
HMC FAIR Friday in coop. with HIDA
|
|
ML@Hereon Episode 42: Paint-by-numbers - Connect the little dots to forecast weather
|
|
Helmholtz Open Science Forum: Open Science und Transfer
|
|
Introduction to Python (3)
|
|
Analyzing and Visualizing Geospatial Data with MATLAB
|
|
Data Science with MATLAB
|
|
Software Development Practices with MATLAB
|
|
Fundamentals of scientific metadata - why context matters
|
|
Mixed Models
|
|
Version control using Git and RStudio
|
|
Imaging - From Organisms to Molecules
|
|
HMC FAIR Friday in coop. with HIDA
|
|
Statistical Models with R
|
|
Imaging - From Organisms to Molecules
|
|
Imaging - From Organisms to Molecules
|
|
Imaging - From Organisms to Molecules
|
|
Imaging - From Organisms to Molecules
|
|
Imaging - From Organisms to Molecules
|
|
Imaging - From Organisms to Molecules
|
|
First Steps in Python
|
|
HIDA Lectures @ HEIBRiDS: Title: "The Data Donation Project - How wearable sensors can help in dealing with the COVID-19 crisis"
|
|
Helmholtz AI Conference 2022
|
|
Helmholtz Imaging Conference 2022
|
|
ML@Hereon: Episode 45 "Data-driven discovery of Governing Equations"
|
|
Data Science Colloquium on Aprilr 21st, 2021 | “Statistical Challenges in Protein Dynamics Modelling”
|
|
Helmholtz AI CountMeIn Challenge
|
|
ML@Hereon: Episode 46 "Mapping to the Windows"
|
|
HMC FAIR Friday in coop. with HIDA
|
|
EU Reform Research Assessment
|
|
Helmholtz Entrepreneurs – From Idea to I Did
|
|
Incubator Summer Academy - From Zero to Hero
|
|
Applying Data Science
|
|
Enabling reproducibility in data science - learn why it matters and how you can do it
|
|
Introduction to OOP in Python
|
|
Continuous Integration in GitLab
|
|
MLE School 2022
|
|
TEACH 2 - Open Up!
|
|
HMC FAIR Friday in coop. with HIDA
|
|
First steps in Python
|
|
Visual Communication of Science
|
|
Continuous Integration in GitLab
|
|
AI, Neuroscience and Hardware: From Neural to Artificial Systems and Back Again
|
|
Data Science Colloquium on June 23rd, 2022 | HIDA Lectures @ DASHH | “Leveraging AI for Science"
|
|
A Crash Course on Semantics and Knowledge Representation
|
|
Enterprise Data Landscapes: Data Lakes and Data Marketplaces
|
|
Dimension-reduction and data visualisation; applications and challenges in single-cell biology
|
|
Carpentries Workshop on Genomics
|
|
HMC FAIR Friday in coop. with HIDA
|
|
Incubator Summer Academy: Introduction to Python
|
|
Incubator Summer Academy: Introduction to Git
|
|
Incubator Summer Academy: Sharing Scientific Software Solutions Across Tools and Domains with Helmholtz Imaging Solutions
|
|
Incubator Summer Academy: Reproducible Data Science
|
|
Incubator Summer Academy: Introduction to Gitlab
|
|
Incubator Summer Academy: Data Science with Python (Pandas)
|
|
Incubator Summer Academy: Fundamentals of Scientific Metadata
|
|
Incubator Summer Academy: Data Challenge
|
|
Incubator Summer Academy: HIDA Networking event
|
|
ML@Hereon: Episode 49 "Recovering Ancient History"
|
|
Survival Analysis
|
|
Incubator Summer Academy: Helmholtz Career Corner
|
|
Incubator Summer Academy: Introduction to Interpretable Machine Learning
|
|
Incubator Summer Academy: Introduction to GitLab CI
|
|
Incubator Summer Academy: Visualization with Python (matplotlib)
|
|
Incubator Summer Academy: Machine Learning-Based Biomedical Image Analysis
|
|
Incubator Summer Academy: Introduction to Machine Learning
|
|
Incubator Summer Academy: Introduction to Napari
|
|
Incubator Summer Academy: Machine Learning for Instance Segmentation and Tracking
|
|
Incubator Summer Academy: Helmholtz Imaging for you!
|
|
Incubator Summer Academy: Introduction to Statistical Learning
|
|
Incubator Summer Academy: Foundations of Research Software Publication
|
|
Incubator Summer Academy: Helmholtz Entrepreneurs: From Idea to I did
|
|
Incubator Summer Academy: Imaging Metadata
|
|
Incubator Summer Academy: Introduction to Deep Learning
|
|
Incubator Summer Academy: Introduction to Statistical Learning
|
|
2nd AI-Hero Hackathon on Energy Efficient AI
|
|
Incubator Summer Academy: Opening session
|
|
Incubator Summer Academy: Introduction to Git
|
|
Fundamentals of scientific metadata: why context matters
|
|
Fundamentals of scientific metadata: why context matters
|
|
First steps in Python
|
|
Object-oriented Programming in Python
|
|
Helmholtz Career Day for Data Science and IT
|
|
Foundations of Research Software Publication
|
|
Software Carpentry (Software Carpentry (Shell, Git, R for Reproducible Scientific Analysis)
|
|
RMarkdown
|
|
Helmholtz Open Science Forum: Publikationskostenmanagement
|
|
Meeting on EOSC Task Forces and exchange with EOSC Secretariat on the EOSC Focus project
|
|
2nd Practice Forum Research Data Management
|
|
3. Helmholtz Open Science Forum: Forschungssoftware
|
|
Scientific Data Curation in Research Field Matter
|
|
Scientific Data Curation in Research Field Matter (Basics)
|
|
On-site AI consultance event at Forschungszentrum Jülich
|
|
65th Helmholtz Open Science Online Seminar
|
|
Hackathon - Developing New Battery Strategies
|
|
First Steps in Python
|
|
Data Science & Health
|
|
Introduction to Indico
|
|
HMC FAIR Friday in coop. with HIDA
|
|
Computational Health Seminar: Dana Pe'er
|
|
Directions in Interpretability - Ruth Fong (HEIBRiDS Lecture Series)
|
|
14th Data Science Colloquium | "Investigating Solid-Liquid Interfaces Using High-Dimensional Neural Network Potentials"
|
|
Introduction to OOP in Python
|
|
Using Containers in Science
|
|
15th Data Science Colloquium | "Building Foundations for Scientific Machine Learning at Scale"
|
|
66th Helmholtz Open Science Online Seminar
|
|
Reconstructing brain sources and their interactions from M/EEG recordings - Stefan Haufe (HEIBRiDS Lecture Series)
|
|
Becoming a Scientific Writer - Putting Why before How
|
|
Introduction to R
|
|
Software Carpentry (Shell, Git, Plotting and Programming in Python)
|
|
Statistical Models with R
|
|
Introduction to Statistics
|
|
Graphics with R
|
|
Multivariate Statistics 1
|
|
Mixed Models
|
|
RMarkdown
|
|
Introduction to Statistics using Python
|
|
Introduction to R
|
|
Statistical Models with R
|
|
Graphics with R
|
|
RMarkdown
|
|
Multivariate Statistics 1
|
|
Multivariate Statistics 2
|
|
Introduction to OOP in Python
|
|
First Steps in Python
|
|
Foundations of Research Software Publication
|
|
Introduction to Git and GitLab
|
|
Ingmar Posner: Learning to Perceive and to Act – Disentangling Tales from (Structured) Latent Space - HEIBRiDS lecture series
|
|
Convolutional Neural Networks - a Big Picture Introduction
|
|
Love your data? Make it reproducible! A workshop on reproducibility in data science
|
|
Introduction to Indico (Event Management)
|
|
Data Processing with Pandas
|
|
Generating Plots with Matplotlib
|
|
First Steps in Python
|
|
Data Carpentry Genomics
|
|
HiRSE Seminar Series - Jupyter Notebooks for RSE and HPC
|
|
HMC FAIR Friday with Britta Dreyer
|
|
HiRSE Seminar Series - Community Building for Research Software Engineering through Podcasting
|
|
Software Carpentry (Shell, Git, R for Reproducible Scientific Analysis)
|
|
Software Development Practices with MATLAB
|
|
Parallel Computing with MATLAB
|
|
HiRSE Seminar Series - 'Scientific software on the permanent edge of production'
|
|
Continuous Integration in GitLab
|
|
Software Carpentry Workshop at KIT
|
|
Helmholtz Open Science Forum “Scholar-led-Publishing in Helmholtz”
|
|
Incubator Summer Academy
|
|
Helmholtz Open Science Forum “Research Evaluation, Reputation Systems, and Openness”
|
|
RSE Bootcamp Part 1/3: Python
|
|
Helmholtz Open Science Forum “Research Evaluation, Reputation Systems, and Openness”
|
|
Six Main Tasks in Image Processing
|
|
5th Summer School in Medical Physics 2023: Data Science and Machine Learning in Radiotherapy
|
|
HiRSE Seminar Series - Increasing the visibility of Research Software: the Helmholtz Research Software Directory.
|
|
Ocean/Atmosphere Time Series Analysis: Theory and Practice
|
|
2nd AI-HERO Hackathon on Energy-Efficient AI
|
|
Data Analysis Intensive
|
|
HiRSE Seminar Series - Code execution during peer review: CODECHECK and RSE reviewers.
|
|
RSE Bootcamp Part 2: Version control & project management
|
|
Software Carpentry (Shell, Git, Plotting and Programming in Python)
|
|
RSE Bootcamp Part 2/3: Version control & project management
|
|
First Steps in Python
|
|
HiRSE Seminar Series - Leveraging the SQAaaS platform to adopt and get recognition for quality practices in software development.
|
|
Helmholtz Entrepreneurs: From Idea to I Did - Turn your Data Science into Business
|
|
HiRSE Seminar: Can Software Metrics Improve Software Quality?
|
|
KCDS Summer School 2023 on Stochastic and Hybrid Modeling
|
|
3. Helmholtz Open Science Forum on the NFDI: Inside Perspectives from the Centers
|
|
Show me the Data: From Data to Insights and Stories with Visualizations
|
|
HiRSE Seminar Series - Can Software Metrics Improve Software Quality?
|
|
Knowledge Representation with the Semantic Web and Knowledge Graphs
|
|
Introduction to Python
|
|
Helmholtz TEACH Conference
|
|
RSE Bootcamp Part 3: Continuous Integration (CI)
|
|
4. Open Science Forum Forschungssoftware
|
|
CERN/NASA Summit: “Accelerating the Adoption of Open Science”
|
|
Deep Learning - Recent Advances in Kernel Methods for Neural Networks
|
|
Reproducibility in Science (Course package at Incubator Summer Academy)
|
|
Introduction to Statistical Learning (Course package at Incubator Summer Academy)
|
|
Python (Course package at Incubator Summer Academy)
|
|
Introduction to Machine Learning (Course package at Incubator Summer Academy)
|
|
Introduction to Explainable AI and ML Fairness (Course package at Incubator Summer Academy)
|
|
Machine Learning- based Image Analysis (Course package at Incubator Summer Academy)
|
|
Introduction to Deep Learning (Course package at Incubator Summer Academy)
|
|
Version Control & Project Management (Package at Incubator Summer Academy)
|
|
Introduction to Scientific Metadata (Course Package at Incubator Summer Academy)
|
|
Machine Learning for Instance Segmentation (Package at Incubator Summer Academy)
|
|
Continuous Integration (Course package at Incubator Summer Academy)
|
|
Regularization in Image Reconstruction: From Model to Data Driven (Course package at Incubator Summer Academy)
|
|
Entrepreneurship: From Idea to I did (Course package at Incubator Summer Academy)
|
|
First steps in Python
|
|
MLE Days 2023 - Summer School and Conference for Machine Learning in Engineering
|
|
Humboldt IP Days
|
|
1st Conference on Research Data Infrastructure (CoRID)
|
|
open-access.network: Workshop "Finanzierungsströme für die Open-Access-Transformation – Überblick und Stand der Diskussion"
|
|
Forum: Bericht zur Entwicklung bzw. Implementierung von Forschungsdaten-Policies in Helmholtz 2023
|
|
Satelliten-Konferenz „Wissenschaftsgeleitetes Open-Access-Publizieren“ zu den Open-Access-Tagen 2023
|
|
Workshop zum Thema "PIDs für Textpublikationen"
|
|
Helmholtz Open Science Office auf dem 4. Helmholtz Sustainability Summit
|
|
19th HiRSE Seminar - 'Research Software, Software Research, and more'
|
|
Building and Manage Events on events.hifis.net
|
|
Helmholtz Reproducibility Workshop
|
|
20th HiRSE Seminar - All you need to know about Software Licenses as an Research Software Engineer (RSE)
|
|
First Steps in Python
|
|
Pandas + Matplotlib
|
|
Helmholtz Career Day for Data Science and IT
|
|
The future of governing equations (HIDA Lecture @ HEIBRIDS)
|
|
MarDATA Online Lecture Series: "Deep Learning from Heterogeneous Big Geospatial Data"
|
|
"Data Science & Health" Lecture Series
|
|
22nd HiRSE Seminar - Enabling Open and Reproducible Science Through Community-Driven Training with The Carpentries
|
|
HUMAN VIRTUOSITY AND AI – BOOSTER FOR MUSICAL CREATIVITY?
|
|
Fundamentals of scientific metadata: why context matters
|
|
67th Helmholtz Open Science Online Seminar
|
|
Helmholtz Reproducibility Workshop
|
|
Online-Workshop: Monitoring von Forschungsdaten-Publikationen – Stand und Perspektive
|
|
Virtuelle Podiumsdiskussion „Offene Infrastrukturen für Open Science“
|
|
MarDATA Online Lecture Series: Creating Probabilistic Forecasts Using Interpretable Machine Learning
|
|
21st HiRSE Seminar: Docs-as-code: how to write documentation with developers.
|
|
HMC FAIR Friday - The WorldFAIR project
|
|
Artificial Intelligence – Opportunities and Risks for Applications in Sustainability and Healthcare
|
|
Software Carpentry (Shell, Git, Programming with R)
|
|
23rd HiRSE Seminar - 'US-RSE: Envisioning the Next Stage and Defining Next Steps'
|
|
Introduction to R
|
|
Graphics with R
|
|
Statistical Models with R
|
|
Introduction to Statistics
|
|
First steps with Python
|
|
Test Event
|
|
Second Forum on Open Science and Transfer
|
|
Helmholtz 2024 GPU Hackathon
|
|
68th Helmholtz Open Science Online Seminar: Science Tracking
|
|
Software Carpentry Workshop (Shell, Git, Programming with R)
|
|
Survival Analysis - How to analyze time-to-event data
|
|
24th HiRSE Seminar - 'Best practice made easy: Deploying tools for FAIR research software development'.
|
|
Kickstart Shell & Git
|
|
Towards Open Digital Research Ecosystems – Interconnecting Infrastructures
|
|
Towards Open Digital Research Ecosystems – Interconnecting Infrastructures
|
|
RMarkdown
|
|
Multivariate Statistics 1
|
|
Multivariate Statistics 2
|
|
Mixed Models
|
|
Introduction to R
|
|
Introduction to Statistics
|
|
Graphics with R
|
|
Statistical Models with R
|
|
RMarkdown
|
|
Mixed Models
|
|
First Steps with Python
|
|
Kickstart Python
|
|
First Steps with Python
|
|
Kickstart R
|
|
First Steps with Python
|
|
Kickstart Shell & Git
|
|
Data processing with Pandas & Data plotting with Matplotlib
|
|
Data processing with Pandas & Data plotting with Matplotlib
|
|
Data processing with Pandas & Data plotting with Matplotlib
|
|
Data processing with Pandas & Data plotting with Matplotlib
|
|
Data processing with Pandas & Data plotting with Matplotlib
|
|
Kickstart Python
|
|
Kickstart Python
|
|
First Steps with Python
|
|
Kickstart Shell & Git
|
|
Kickstart R
|
|
HMC FAIR Friday: The eFAIRs project - Enhancing FAIRness in seismological data management with Dr. Angelo Stroll
|
|
25th HiRSE Seminar - What RSEs should know about software citation.
|
|
Introduction to Git and GitLab
|
|
Introduction to Git and GitLab
|
|
Introduction to Git and GitLab
|
|
Introduction to Git and GitLab
|
|
Foundations of Research Software Publication
|
|
Foundations of Research Software Publication
|
|
Continuous Integration (CI)
|
|
Continuous Integration (CI)
|
|
Continuous Integration (CI)
|
|
Analyzing and Visualizing Geospatial Data with MATLAB
|
|
Data Science with MATLAB
|
|
Clean Code Practices with MATLAB for Sustainable Research Software
|
|
Fundamentals of Scientific Metadata: Why Context Matters
|
|
Software Carpentry Workshop (Shell, Git, R for Reproducible Scientific Analysis )
|
|
26th HiRSE Seminar - JOSS: A journal for open source software that is an open source software project.
|
|
HIDA Lecture Series "AI and Large Language Models" - ChatGPT's Backgrounds: Exploring the World of Large Language Models
|
|
HIDA Lecture Series "AI and Large Language Models" - Ethical considerations on hate speech and AI
|
|
Object-Oriented Programming (OOP)
|
|
Object-Oriented Programming (OOP)
|
|
Object-Oriented Programming (OOP)
|
|
Object-Oriented Programming (OOP)
|
|
27th HiRSE Seminar - Dr Matthias Kiesselbach (DFG) - 'Research Assessment – the international reform discussions, and DFG‘s position'
|
|
Helmholtz Imaging Conference 2024
|
|
AI for Life Scientists: from Basics to Applications
|
|
HIDA Lecture Series "AI and Large Language Models" - Contextualizing LLMs – What are the social and ethical implications?
|
|
16th Data Science Colloquium | "Neural Approaches to Optimal Transport"
|
|
HMC FAIR Friday: HELIPORT & ALAMEDA: Two platforms to ease your reasearch project & metadata management life!
|
|
RSE Summer School 2024
|
|
69th Helmholtz Open Science Online Seminar - Open Hardware: Bringing scientific instruments back into the open science conversation
|
|
Fundamentals of scientific metadata: why context matters
|
|
Mixed Models
|
|
Helmholtz Summer School - From Data to Knowledge
|
|
Basics of Python
|
|
Wissenschaftliche Publikationen sicher nutzen mit Creative Commons Lizenzen
|
|
HMC FAIR Friday: Discipline-specific options and standardized output of F-UJI with Dr. Robert Huber
|
|
29th HiRSE Seminar - Learnings from SURESOFT - Research Software Engineering Beyond Tooling.
|
|
Applications of computer vision in dentistry
|
|
Data Science Unlocked: Helmholtz Platforms Roadshow
|
|
HIDA Lecture @MarDATA: "Leveraging Digital Twins in Ocean Science: Bridging Real-World Systems and their Virtual Simulations"
|
|
Scientists – The Secret Heroes of the Startup World
|
|
MarDATA Workshop: "Ensemble-Based Data Assimilation: Concepts, Methods, and Hands-On Tutorials"
|
|
Low-rank Methods in Visual Computing and Machine Learning
|
|
31st HiRSE Seminar: 'Research Software Engineering and Software Engineering Research: Bridging Knowledge Gaps'
|
|
HiRSE Seminar: 'Better Software Architecture, Better Software, Better Research' by Professor Wilhelm Hasselbring
|
|
HIDA Lecture Series "AI and Large Language Models" - Challenges and Threats in Generative AI: Exploits and Misuse
|
|
KCDS Workshop on Data Processing and Data Assimilation 2024
|
|
Helmholtz Summer School: Introduction to FAIR and Reusability of Scientific Data
|
|
Helmholtz Summer School: Introduction to Scientific Metadata
|
|
Helmholtz Summer School: Introduction to Machine Learning with scikit-learn
|
|
Helmholtz Summer School: Introduction to Statistical Learning
|
|
Helmholtz Summer School: Introduction to Uncertainty Quantification (UQ) in ML
|
|
Helmholtz Summer School: Explainable Artificial Intelligence
|
|
Helmholtz Summer School: A practical guide to dimensionality reduction
|
|
Helmholtz Summer School: Large Language Models
|
|
Helmholtz Summer School: Regularization in Image Reconstruction: From Model to Data Driven Methods
|
|
Helmholtz Summer School: Introduction to Image Registration
|
|
Helmholtz Summer School: 3D visualization
|
|
Helmholtz Summer School: First steps with Python
|
|
Helmholtz Summer School: Time-dependent Generative Models
|
|
Helmholtz Summer School: Fantastic Vision Language Models and how to compress them
|
|
Helmholtz Summer School: Data processing with Pandas & Data plotting with Matplotlib
|
|
Helmholtz Summer School: Entrepreneurship: From Idea to I did
|
|
Helmholtz Summer School: Introduction to Git and GitLab
|
|
Helmholtz Summer School: Continuous Integration with GitLab
|
|
Helmholtz Summer School: Fairness in Machine Learning
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HMC FAIR Friday: The origin of data – The relevance of provenance in the context of FAIR
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ChatGPT & Gen AI Training for Researchers
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RainQuest Hackathon: Precipitation Estimation from Weather Radar Data
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Helmholtz Summer School: From Idea to I Did: Empowering Women Entrepreneurs
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RainQuest Hackathon: Precipitation Estimation from Weather Radar Data
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Introduction to Machine Learning
|
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HIDA Lecture Series "AI and Large Language Models" - ChatGPT in Action: Enhancing Your Workflow
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HIDA Lecture: “Empowering Women Entrepreneurs”
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Deep Learning in Inverse Problems Workshop
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Paris Conference on Open Research Information
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RDA 23rd Plenary Meeting
|
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32nd HiRSE Seminar - Helmholtz Software Award 2023: the winners present their software.
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Research Ethics in the Age of AI: Embracing Openness as a Path Forward
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MSS & JARA CSD Workshop
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Helmholtz Summer School - From Data to Knowledge
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Introduction to R
|
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Test Event für Jonas
|
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Coping with Stress at the University and Beyond
|
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4. Helmholtz Reproducibility Workshop
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Introduction to Git and GitLab
|
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Introduction to Machine Learning
|
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Data processing with Pandas & Data plotting with Matplotlib
|
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Research Ethics in the Age of AI: Embracing Openness as a Path Forward
|
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Kickstart Python
|
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Introduction to Statistics
|
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HIDA Lecture Series "AI and Large Language Models" - ChatGPT in Action: Enhancing Your Workflow
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HIDA Lecture “Empowering Women Entrepreneurs”
|
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HIDA Lecture Series "AI and Large Language Models" - TrustLLM - Towards Trustworthy and Factual Language Models
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HIDA Lecture Series "AI and Large Language Models" - A Short Introduction to Efficient Natural Language Processing
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Register here to be informed about open course seats
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Hackathon „Hearts Gym” 2024
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Test
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Introduction to Git and GitLab
|
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Mixed Models
|
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Object-Oriented Programming (OOP)
|
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TEACH 4 _ TRIAL
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Data processing with Pandas & Data plotting with Matplotlib
|
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Continuous Integration (CI)
|
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RMarkdown
|
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Foundations of Research Software Publication
|
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Statistical Models with R
|
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Kickstart R
|
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Kickstart Shell & Git
|
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Graphics with R
|
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First Steps with Python
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Data Science & Health Lecture Series
|
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RMarkdown
|
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Version Control using Git and RStudio
|
|
Data Science & Health Lecture Series
|
|
Where-To-Play Market Explorer
|
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34th HiRSE Seminar - Mihaela Jarema (Mathworks) - 'Journey to FAIR Research Software with MATLAB'
|
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35th HiRSE Seminar - Ann Gledson (University of Manchester) - 'Agile Methods for RSEs'
|
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Mixed Models
|
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Multivariate Statistics 2
|
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3rd International Workshop on Reinforcement Learning for Autonomous Accelerators (RL4AA’25)
|
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Legal Challenges in Setting up your Start-up: Pitfalls, Obstacles and Best Practices
|
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HMC FAIR Friday: HERMES: FAIRer Software Publication Through Richer Metadata
|
|
MarDATA workshop "Transformers and Generative AI"
|
|
Legal Challenges in Setting up your Start-up: Pitfalls, Obstacles and Best Practices
|
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Legal Challenges in Setting up your Start-up: Pitfalls, Obstacles and Best Practices
|
|
matRad User Meeting & Hackathon 2025
|
|
Helmholtz Open Science Office – Enabling Open Science at Helmholtz
|
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36th HiRSE Seminar - 'The Teaching RSE project - Towards a professionalisation of RSE Education'
|
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HIDA Lecture: The Ethics of AI: Foundations of Applied Ethics and Emerging Risks from AI Development
|
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HIDA Lecture: Machine Learning for Precision Medicine: Avenues and Roadblocks
|
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4. Helmholtz Reproducibility Workshop
|
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First Steps in Python
|
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1. Forum Helmholtz Research Data Commons
|
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37th HiRSE Seminar - 'Integrated Continuous Benchmarking'
|
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HIDA Lecture: Large-Scale Brain Decoding - Taking Advantage of Physiological Diversity
|
|
Market Mastery: Identifying Ideal Customers and Effective Online Marketing Strategies
|
|
Introduction to R
|
|
Introduction to Git and GitLab
|
|
Reusability of Scientific Data for Matter
|
|
Object-Oriented Programming (OOP)
|
|
Lecture: AI and the Future of Research: Stakeholders, Process, and Practices
|
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Workshop: What Will it Take to Succeed at Research? Taking Reproducibility to Action for Transformative AI-and Data-enabled Scientific Research
|
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Computational Genomics
|
|
RMarkdown
|
|
4. Helmholtz Open Science Forum on the NFDI: Helmholtz Contributions to FAIRness and Data Quality
|
|
Kickstart R
|
|
Kickstart Shell & Git
|
|
First Steps in Python
|
|
Overview of AI's Parallelization Methods in Supercomputers
|
|
Introduction to Statistics
|
|
70th Helmholtz Open Science Online Seminar
|
|
Software Quality Assurance at Helmholtz - 6. Helmholtz Research Software Forum
|
|
Continuous Integration (CI)
|
|
Graphics with R
|
|
Kickstart Python
|
|
Introduction to Machine Learning
|
|
Fundamentals of Scientific Metadata for Health
|
|
Mixed Models
|
|
Basic Methods in Machine Learning
|
|
Introduction to R
|
|
Introduction to Git and GitLab
|
|
Data Processing with Pandas and Visualization with Matplotlib
|
|
Introduction to Git and GitLab
|
|
A Practical Guide to Dimensionality Reduction
|
|
Introduction to Explainable AI
|
|
Multivariate Statistics 1
|
|
Fundamentals of Scientific Metadata for Energy
|
|
Advanced Methods in Machine Learning
|
|
Kickstart Python
|
|
Foundations of Research Software Publication
|
|
Kickstart Shell & Git
|
|
Introduction to Machine Learning
|
|
AI Ethics: Model Cards for Model Reporting
|
|
Kickstart R
|
|
First Steps in Python
|
|
Continuous Integration (CI)
|
|
Multivariate Statistics 2
|
|
Kickstart Python
|
|
Data Processing with Pandas and Visualization with Matplotlib
|
|
Shiny Apps with R
|
|
Introduction to R
|
|
Overview of AI's Parallelization Methods in Supercomputers
|
|
18th Data Science Colloquium
|
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38th HiRSE Seminar - 'Software Management Plans: how do they lead to better research?'
|
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KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
JSC OpenStack training (training course, online)
|
|
Einführung in ParaView zur Visualisierung von wissenschaftlichen Daten (training course, online)
|
|
Bringing Deep Learning Workloads to JSC supercomputers (training course, online, 1st run)
|
|
Parallel programming with OpenMP
|
|
Introduction to Bayesian Statistical Learning (training course, online)
|
|
GPU Programming Part 1: Foundations (training course, on-site)
|
|
Interactive High-Performance Computing with JupyterLab (training course, online)
|
|
HIDA Lecture: GenAI in the Public Sector: The Now & Next of Applications
|
|
Helmholtz Imaging Conference 2025
|
|
Introduction to parallel programming with MPI
|
|
MOLS Lecture: Insights from AI4OCEANS: Advancing Knowledge with AI Solutions for Ocean and Climate Challenges
|
|
Version Control using Git and RStudio
|
|
Survival Analysis - How to analyze time-to-event data
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
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KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
Helmholtz-ELLIS Workshop on Foundation Models in Science
|
|
39th HiRSE Seminar - 'Introduction of a quality indicator for research software publications'
|
|
HIDA PhD Kick - Off Days
|
|
Introduction to Unreal Engine for Science (ONLINE course)
|
|
Data Analysis and Plotting in Python with Pandas (ONLINE course)
|
|
EU Regional School - Mathematical Theory of Finite Elements (A Crash Course for Engineers)
|
|
Lecture Robyn Clay-Williams "We are all Individuals: Considering User Diversity in Design"
|
|
40th HiRSE Seminar - 'CodeRefinery: A Community for Teaching, Learning, and Growing Together' with Samantha Wittke
|
|
HIDA Lecture: AI, Responsibility Gaps, and Asymmetries between Credit and Blame
|
|
Workshop Robyn Clay-Williams: "We are all Individuals: Considering User Diversity in Design"
|
|
Fail Fast, Learn Faster: Top 10 Startup Mistakes & What They Teach Us
|
|
HIDA CIFAR Summer School on Data Science & Climate
|
|
Programming in C++ (training course, on-site)
|
|
Introduction to Bayesian Statistical Learning 2 (training course, online)
|
|
High-performance computing with Python
|
|
Bringing Deep Learning Workloads to JSC supercomputers (training course, online, 2nd run)
|
|
Data Science Colloquium | “Recent Progress on Inertial Fusion Ignition at the National Ignition Facility and the Path Ahead”
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
Connect, Convince, Collaborate: The Art of Stakeholder Management & Networking
|
|
Business Model Development - Approach and Tips
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
What is a Business Model? About the Business Model Canvas and Business Model Patterns
|
|
The Fastest Way to Validate Your Idea
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
Plan - Heat - Win! How to build up a sales concept
|
|
HMC FAIR Friday: "A FAIR-enabling resource for biodiversity monitoring schemes" | Annegret Grimm-Seyfarth
|
|
2nd International Summer School on Advanced Soil Physics: Soil-Plant-Water Flow
|
|
Bridging the Gap: Research & Real-World Needs
|
|
Smart Startups: Leveraging AI & Digital Tools for Founders
|
|
DESY Start-up School 2025
|
|
HIDA Lecture: Clinical Large Language Models in Healthcare – Applications, Challenges, and Opportunities
|
|
Bridging the Gap Between Private Data and AI: A Beginner’s Guide to Retrieval Augmented Generation (RAG)
|
|
Fundamentals of Scientific Metadata: Why Context Matters
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
KI in Verwaltung & Management: ChatGPT & Co effektiv nutzen
|
|
Introduction to Supercomputing at JSC - Theory & Practice (training course, online)
|
|
GPU programming Part 2: Advanced GPU Programming (training course, online)
|
|
Introduction to parallel programming with MPI and OpenMP (training course)
|
|
HMC FAIR Friday: "FAIR research data management in composite engineering within the MEMAS project" with Mathieu Vinot, DLR
|
|
HMC FAIR Friday: "A place for everything: traceable science using metadata from syntheses and characterisation" with Brian R. Pauw
|
|
HMC FAIR Friday: "Distance and Data Reuse" with Paul Groth
|
|
Digital Twins in the Life Sciences: Turning Raw Data into Dynamic Models
|
|
KCDS Summer School on Gaussian Processes and Neural Operators
|
|
42nd HiRSE Seminar - Meet the "Young RSE Award' winners
|
|
HIDA Lecture: Machine Learning for Monitoring Sustainability in the Corporate and Public Sector
|
|
In-Situ Visualization on High-Performance-Computers (ONLINE course)
|
|
Bringing Deep Learning Workloads to JSC supercomputers
|
|
Virtual Worlds for Machine Learning
|
|
HDS-LEE Retreat 2025
|
|
First Steps in Python
|
|
Six Main Tasks in Image Processing
|
|
Introduction to Deep Learning
|
|
**POSTPONED** 43rd HiRSE Seminar - Leveraging Earth System Science to Exascale with Sabine Griessbach
|
|
AI Ethics: Model Cards for Model Reporting
|
|
Introduction to Git and GitLab
|
|
Overview of AI's Parallelization Methods in Supercomputers
|
|
Object-Oriented Programming (OOP)
|
|
Introduction to Statistics
|
|
Become a certified data science instructor
|
|
HIDA Lecture: Fostering Research Integrity in an AI-Driven World
|
|
Kickstart Shell & Git
|
|
Introduction to Uncertainty Quantification in ML
|
|
A Practical Guide to Dimensionality Reduction
|
|
Regularization in Image Reconstruction: From Model to Data Driven Methods
|
|
RMarkdown
|
|
Continuous Integration (CI)
|
|
Data Processing with Pandas and Visualization with Matplotlib
|
|
First Steps in Python
|
|
Graphics with R
|
|
Introduction to Explainable AI
|
|
Introduction to Image Registration
|
|
Mixed Models
|
|
Kickstart Python
|
|
Foundations of Research Software Publication
|
|
Fundamentals of Scientific Metadata: Why Context Matters
|
|
3D Data Visualisation
|
|
Reproducible and Open Research
|
|
Understanding Transformers
|
|
Object-Oriented Programming (OOP)
|
|
Introduction to Git and GitLab
|
|
First Steps in Python
|
|
Overview of AI's Parallelization Methods in Supercomputers
|
|
Introduction to Deep Learning
|
|
Continuous Integration (CI)
|
|
44th HiRSE Seminar - Research practices in a digitalized world: Research software, mundane software and programming languages in research
|
