teaching

We will be offering master courses in the field of materials data science and informatics within the Chair of Data Science and Computer Science in Materials Science at RWTH Aachen University soon. Stay tuned!

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Introduction to Data Mining and Machine Learning

Data mining and data analysis plays a growing role for the extraction of information both from simulations and experiments/microscopy. This requires knowledge of the algorithms and methods, the underlying statistical/probabilistic concepts as well as the ability to practically use such methods, e.g. through programming.

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Materials Data Science and Informatics

This module focuses on methods and practical implementations for using data science approaches to extract new information and knowledge from situations of materials scientific relevance. Used methods ranges from dimensionality reduction methods through various deep learning architectures (drop-out, convolutional networks, autoencoder, recurrent and generative adversarial networks) to approaches for high- throughput data analyze (e.g., image data from microscopy) or the use of tailored machine learning methods for predicting materials with new properties.

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From Molecular to Continuum Physics I

more information coming soon...

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Last Modified: 30.01.2023