Join us in the opening of the Incubator Summer Academy!
This event will be take place via Zoom.
→ Register here ←
Note: Due to huge demand we will offer this event also on 6., 9. and 12. September. Please choose the date that best suits you when registering.
In this workshop, participants will learn how to work with the Python programming language. We will introduce the basic building blocks needed to "make the computer do stuff" and lay a solid basis for future self-guided learning or more...
The workshop provides a solid introduction into the practical usage of the version control system Git in combination with the collaboration platform GitLab.
This workshop will cover the following topics:
- Introduction to version control
- Git setup
- Basic local Git workflow
- Branching and merging
- Resolving Conflicts
→ **[Register...
Brief content:
1. Simplifying reproducibility for users and authors of scientific tools
2. Introduction to Helmholtz Imaging Solutions and Album
3. Basics of using Helmholtz Imaging Solutions
4. Writing your own Helmholtz Imaging Solution
5. Publishing solutions in a catalog
→ Register here ←
Topics:
- What is reproducible research?
- Reproducible research practices
- Project organisation for reproducible research
- Reproducible analyses
This course will span over two days. The second half will be on September 14 at 2 pm.
→ Register here ←
In this course we will look at the intricate relationship between (digital) research data, metadata and knowledge, discuss why metadata is critical in today’s research, as well as explain some of the technologies and concepts related to structured machine-readable metadata.
Have you ever struggled to make sense of scientific data provided by a collaborator - or even understanding your own...
This workshop provides a practical introduction into GitLab.
In detail, we cover the following topics:
- Overview about GitLab
- Working with the Git repository
- Planning tasks using Issues
- Collaboration using Merge Requests
- Overview of advanced functionalities
→ Register here ←
In this quick workshop we will get an overview over the data science framework pandas.
Participants should have some fundamental knowledge on how to work with Python and have a working Python-installation ready and the pandas-package installed.
The workshop contains a code-along introduction and a introduces a set of exercises to build some practical experience.
Instructors will be...
Topics:
- What is reproducible research?
- Reproducible research practices
- Project organisation for reproducible research
- Reproducible analyses
This is day two of the course starting on September 13 at 1 pm.
In this course we will look at the intricate relationship between (digital) research data, metadata and knowledge, discuss why metadata is critical in today’s research, as well as explain some of the technologies and concepts related to structured machine-readable metadata.
Have you ever struggled to make sense of scientific data provided by a collaborator - or even understanding your own...
This workshop provides a practical introduction to Continuous Integration (CI) using GitLab CI. It will cover these aspects:
- Setting up a basic CI pipeline with linting and testing.
- Advanced concepts to optimize the CI implementation. With a focus on
- Performance
- Reducing Redundancies
- Concise pipeline definition and cross-project reuse.
- Optional: Other useful...
In this quick workshop we will get an overview over the data visualization framework matplotlib.
Participants should have some fundamental knowledge on how to work with Python + pandas and have a working Python-installation ready and the pandas and matplotlib-packages installed.
The workshop contains a code-along introduction and a introduces a set of exercises to build some...
This course will introduce participants to the concepts of AI and Machine Learning, covering clustering and clasifications fundamentals as well as practical experience with standard methods for both techniques. Lastly, participants will gain an insight on best practises for evaluating a machine learning model's performance (ROC curve, FPR etc.)
More information can be found here:...
Brief Content:
1. Introduction to Machine Learning-based Image Analysis
2. Applications and Examples on Biomedical Images
3. Introduction to nnU-Net
4. Hands-on Tutorial on how to train and apply nnU-Net (using google colab). The tutorial starts right after this course and will take 45min, number of participants is limited to 30.
→ **[Register...
Brief Content:
This tutorial is designed as a follow-up to the intermediate course "Machine Learning-Based Biomedical Image Analysis" on September 15, 2022 at 10:00 by Paul Jäger et al.
It comprises a hands-on Tutorial on how to train and apply nnU-Net (using google colab). The number of participants is limited to 30.
*Participation in the course "Machine Learning-Based...
This is day two of the course starting on September 15 at 2 pm.
This course will introduce participants to the concepts of AI and Machine Learning, covering clustering and clasifications fundamentals as well as practical experience with standard methods for both techniques. Lastly, participants will gain an insight on best practises for evaluating a machine learning model's performance ...
The purpose of navigation is to determine the position, velocity, and orientation of manned and autonomous platforms, humans, and animals. Obtaining accurate navigation commonly requires fusion between several sensors, such as inertial sensors and global navigation satellite systems, in a model-based nonlinear estimation framework. Recently, data-driven approaches applied in various fields...
From Helmholtz Imaging Modalities to the Helpdesk to Solutions to great images! A quick tour through the Helmholtz Imaging portfolio and how you can exploit our support and services to do your imaging experiments.
→ Register here ←
If you want to join spontaneously, here is the link:
https://desy.zoom.us/j/66379738048 (Kenncode: HI4U)
This is an hands-on introduction to the first steps in Deep Learning, intended for researchers who are familiar with (non-deep) Machine Learning.
The use of Deep Learning has seen a sharp increase of popularity and applicability over the last decade. While Deep Learning can be a useful tool for researchers from a wide range of domains, taking the first steps in the world of Deep Learning...
Metadata for scientific images is crucial for the success of any imaging experiment. What are metadata, where do you find them, how do you exploit them? The use of metadata in imaging highly depends on the domain. In some research areas metadata is already a well established standard while others scribble them in their notebook.
Here we will give an introduction to metadata in imaging,...
This is an hands-on introduction to the first steps in Deep Learning, intended for researchers who are familiar with (non-deep) Machine Learning.
The use of Deep Learning has seen a sharp increase of popularity and applicability over the last decade. While Deep Learning can be a useful tool for researchers from a wide range of domains, taking the first steps in the world of Deep Learning...
What is entrepreneurial thinking and why does it matter?
Entrepreurial thinking is a way of thinking and refers to the capacity to act upon opportunities and ideas, and to transform them into value for others. It is founded upon creativity, critical thinking and problem solving, taking initiative and perseverance and the ability to work collaboratively in order to plan and manage...
The reductive approach which sees health as the rejection of the other - be it cancer or pathogens is false. As we learn more about the individual characteristics of cells in the body and the variable forms of immune responses it becomes ever clearer that we need a new paradigm of study one that considers open systems of interactions across scales of biology rather than defining sharp borders...
We will provide you with actionable advice about how to prepare your research code before publishing it or submitting it alongside a research publication.
This workshop will cover the the following topics:
- Code repository structuring
- Minimum coding practices
- Documentation
- Open source licensing
- Minimum software release practices
- Software citation
We demonstrate the...
based on python, follow-up to the course by Paul Jäger on September 15, 2022.
The course will build on the introduction to convolutional neural networks in Imaging by Paul Jäger, and will cover essential rules for designing your own networks, in particular when dealing with large image data. You will get hands-on experience in setting up and training your own networks for image analysis...
Topics covered involve basic concepts in statistical learning, as well as supervised learning techniques (high-dimensional regression and classification) and unsupervised learning (mixture models and dimension reduction).
→ Register here ←
Topics covered involve basic concepts in statistical searning, as well as supervised learning techniques (high-dimensional regression and classification) and unsupervised learning (mixture models and dimension reduction).
This is day two of the course starting on September 21 at 2 pm.
This 30min slot is optional for those who had problems installing the program.
https://www.napari-hub.org/plugins/devbio-napari#installation
Please do install the programm before!
In case of issues with the installation, attendees can reach out any time – before the course - by opening a thread on https://image.sc...
It is recommended to take a Python-Basics Course before. For example from the first week of this Summer Academy.
In this course we will introduce image processing with Python, Jupyter lab and Napari. Students will learn how to process images interactively in Napari and afterwards how to replicate the same results in Jupyter notebooks. Additionally, the students will get an idea how to...
During this course participants will get an introduction to the topic of Explainable AI (XAI). The goal of the course is to help participants understand how XAI methods can help uncover biases in the data or provide interesting insights. After a general introduction to XAI, the course goes deeper into state-of-the-art model agnostic interpretation techniques as well as a practical session...
Come and join us in the Helmholtz Career Corner in gather.town!
This is the place where you can gather information about career opportunities within the Helmholtz Community- be it the latest job openings or exchange opportunities. Get an overview of the activities of some Helmholtz Centers and platforms, and network with your peers and representatives from the Helmholtz...
Openness is a pillar for good scientific practice and contributes to research integrity. How do metadata fit in here?
About HMC FAIR Friday
To stimulate and support interdisciplinary exchange on FAIR and (meta)data, the Helmholtz Metadata Collaboration (HMC) - in close cooperation with the Helmholtz Information & Data Science Academy (HIDA) - is organising the lecture series....
Teach an agent to play the Hearts card game, get into touch with multi-agent reinforcement learning.
