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DTSTAMP:20260924T225749Z
UID:9d20dd99-5ce1-408b-a401-1806630ead0b
DTSTART:20261130T080000Z
DTEND:20261202T160000Z
DESCRIPTION:Educators:\nDominik March\, Lukas Beierle\, Sonja Diedrich\, Ju
 lian Hahnfeld (BiGi)\n\nDate:\nNov. 30 – Dec. 2\, 2026\n\nLocation:\nGie
 ßen Seltersweg 85\, Bioinformatics Lab\n\nContents:\nIn the first part of
  the course\, we will focus on exploratory data analysis and data preproce
 ssing. The second part will cover the fundamentals of deep learning\, incl
 uding model architectures and training procedures\, and will shift to appl
 ying deep learning models to bioinformatics tasks. In the third part\, you
  will evaluate and visualize the results\, and you will learn about LMMs i
 n biology and AI/GPTs in general.\n\nLearning goals:\n- Overview of the to
 pic of deep learning (with bioinformatics examples)\n- Data analysis and p
 reprocessing for neural network models\n- How to implement and train a neu
 ral network using Keras\n- Large Language Models (LLMs) and pre-trained mo
 dels and how they can be applied to various tasks.\n\nPrerequisites:\n- Go
 od knowledge of Python and the Linux Terminal\n- You can bring your own la
 ptop\, but it's not required\n\nKeywords:\nDeep Learning\, Keras\, Large L
 anguage Models\n\nTools / Libraries / Languages:\nPython\, Keras\, Kerashu
 b
LOCATION:Seltersweg 85\, 85 Seltersweg
SUMMARY:Introduction to Deep Learning 2026
URL;VALUE=URI:https://www.denbi.de/training-courses-2026/2153-introduction-
 to-deep-learning-2026
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