organized in cooperation with Helmholtz Information & Data Science Academy (HIDA) and Helmholtz AI
Introduction to Explainable AI
This 2-half-day course provides an introduction to the topic of Explainable AI (XAI). This fundamental knowledge is to be used as a starting point for self-guided learning during and beyond the course time.
All course days cover alternating sequences of theoretical input and hands-on exercises, which are discussed with the instructors during the course.
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 as well as model-specific interpretation techniques. The practical hands-on sessions will help to learn about strengths and weaknesses of these standard methods used in the field.
Learning Goals
Day 1: Introduction to XAI and XAI for Random Forest
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General introduction to eXplainable AI
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Theory and practical application of the model-agnostic methods Permutation Feature Importance, SHAP and LIME to Random Forest models
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Theory and practical application of the model-specific method FGC to Random Forest models
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Comparison of different XAI methods for Random Forest models
Day 2: XAI for CNNs
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Short introduction to Convolutional Neural Networks (CNNs)
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Theory and practical application of the model-agnostic methods SHAP and LIME to CNN models
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Theory and practical application of the model-specific method Grad-CAM to CNN models for image data
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Comparison of different XAI methods for CNN models
Prerequisites
Basic knowledge of Python. Basic understanding of ML / DL models (Random Forest, CNNs).
Target Group
This course is open to researchers of all career stages, or anyone interested in learning about the subject.
Course Days & Times
May 6, 2025, 10 am - 3 pm
May 7, 2025, 10 am - 3 pm
NOTE: Registration will open April 8, 2025, 12 pm.
Attendance & Certificates
The course content is coordinated, so we strongly recommend that you do not miss any part of the course. To receive a certificate we expect at least 80% attendance and active participation.
Registration & Cancellation
This course is open to individuals affiliated with Helmholtz or a HIDA Partner only.
Your registration for this course is binding. If you need to leave/miss the course for a period of time, please let us know in advance via hida-courses@helmholtz.de.
If you have to cancel the course for any reason, please do so as soon as possible to allow time for others to take your seat. To cancel, please withdraw your registration on the course site or write an email to hida-courses@helmholtz.de.
Additional Information
There is no waiting list for this course! If someone withdraws from a course, their place is automatically reopened. We therefore advise you to keep an eye on the registration in case the course is fully booked and you would like to attend. Also, this course will be offered again in the future - you can check our HIDA course catalog for updates.
This course is free of charge.
