Artificial intelligence, specifically machine learning and deep learning is becoming increasingly important for the evaluation of materials science data, especially for image data.
In this training we offer you a practice oriented introduction to artificial neural networks for the automatic analysis of material science data. The focus will be on the classification and segmentation of image- and table- data.
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.
1st - 5th day 9am-1pm
Required software tools for participation:
PUTTY (participants will receive installation instructions shortly before the training)
Material Engineering Center Saarland - MECS
TU Bergakademie Freiberg
We would be happy to answer your questions about the training personally. Simply call us or send us an e-mail.
Phone.: +49-(0)69-75306 757
Fax: +49-(0)69-75306 733