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04/17/2023 - 04/21/2023 | St. Augustin

Deep Learning - Fundamentals and Applications to Examples in Materials Science

Artificial intelligence in machine learning using deep learning is becoming increasingly important for analyzing materials science data, especially image data.

The training course offers a practice-oriented introduction to convolutional neural networks to automatically analyze material science data. The focus will be on classification and segmentation of image data and tabular data.

Training Chair:

Dr.-Ing. Tim Dahmen - Deutsches Forschungszentrum für Künstliche Intelligenz GmbH


-After a short introduction, which is not mathematically in-depth, application examples of Deep Learning are developed together.

-You will learn how to implement and apply neural networks with the help of Python and suitable libraries. The focus is on the independent application of the developed models.

-By executing and modifying the provided scripts on your own, you will be able to directly apply the acquired knowledge in practice.

-After participation, you will know the possibilities and problems of machine learning, so that you can efficiently transfer and adapt the learned contents to your own data.

Target Group:

Ideal prerequisites for successful participation in the training course are basic programming skills in Python, Matlab or other programming languages. The previous knowledge includes: variables and associated arithmetic operations, functions, case distinctions, control structures. Basic knowledge of mathematics is also helpful. For example, you should have an idea about the keywords vector, linear dependence, gradient and non-linearity.

Information on participating / attending:
Lecture times: 1st - 5th day 9 am - 1 pm
Required software tools for participation: PUTTY (participants will receive installation instructions shortly before the training)


04/17/2023 - 04/21/2023

Event venue:

St. Augustin

Target group:

Business and commerce, Scientists and scholars

Email address:


transregional, national

Subject areas:

Information technology, Materials sciences

Types of events:

Presentation / colloquium / lecture, Seminar / workshop / discussion




Stefan Klein


Kommunikation & Medien

Event is free:


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