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CALSCALE:GREGORIAN
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DTSTAMP:20260808T230103Z
UID:75f78cb7-1e4c-44bd-8385-5d897d9f1953
DTSTART:20241202T090000Z
DTEND:20241203T151500Z
DESCRIPTION:Educators:\nLukas Beierle\, Sonja Diedrich\, Dominik March (BiG
 i)\n\nDate:\nDecember 2nd and 3rd\, 2024.\n\nLocation:\nGießen\n\nContent
 s:\nThe deep learning course offers a comprehensive introduction to essent
 ial concepts and practical applications.\n\nOn the first day\, participant
 s will be welcomed with an overview of the course objectives\, followed by
  foundational insights into deep learning principles and neural networks. 
 The afternoon focuses on the history of deep learning\, practical data pre
 paration and encodings led by Sonja Diedrich\, and hands-on sessions using
  TensorFlow and Keras\, culminating in a real-world end-to-end example.\n\
 nThe second day features a guest talk by Prof. Dr. Andreas Dominik\, a dis
 cussion session\, and an introduction to large language models. The aftern
 oon is dedicated to practical activities with pretrained language models a
 nd regression techniques using neural networks\, finishing with an explora
 tion of deep learning's future in bioinformatics.\n\nThis streamlined cour
 se promises to deepen your understanding of deep learning while equipping 
 you with skills to apply these techniques in various research contexts.\n\
 nMonday\, 02.12.2024\, morning session:\nOnboarding &amp\; Introduction\n
 • 10:00 - 10:30 → Arrival of participants\n• 10:30 - 11:00 → Welco
 me &amp\; introduction\n• 11:00 - 12:00 → Introduction to deep learnin
 g\n• 12:00 - 13:00 → Lunch break\n\nMonday\, 02.12.2024\, afternoon se
 ssion: Deep learning basics\n• 13:00 - 13:30 → History of deep learnin
 g\n• 13:30 - 14:30 → Neural networks\n• 14:30 - 14:45 → Short brea
 k\n• 14:45 - 15:15 → Data preperation &amp\; encodings feat. Sonja Die
 drich\n• 15:15 - 15:45 → Tensorflow and Keras\n• 15:45 - 16:30 → E
 nd-to-End example\n\nTuesday\, 03.12.2024\, morning session: Guest talk &a
 mp\; Hands-on\n• 09:00 - 09:45 → Guest talk: Prof. Dr. Andreas Dominik
 \n• 09:45 - 10:15 → Talk discussion\n• 10:15 - 10:30 → Coffe break
 \n• 10:30 - 11:00 → Recap and hands-on infos\n• 11:00 - 11:45 → Sh
 ort introduction to large language models\n• 11:45 - 12:45 → Lunch bre
 ak\n\nTuesday\, 03.12.2024\, afternoon session: More Hands-on\n• 12:45 -
  14:15 → Pretrained language models hands-on\n• 14:15 - 14:30 → Shor
 t break\n• 14:30 - 15:30 → Regression with neural networks\n• 15:30 
 - 15:45 → Short break\n• 15:45 - 16:15 → Outlook &amp\; deep learnin
 g in bioinformatics 2\n\nLearning goals:\n- Overview of the topic deep lea
 rning (with bioinformatic examples)\n- Understanding the basics of neural 
 networks\n- Know the deep learning project lifecycle\n- Understand the imp
 ortance of data preprocessing\n- Learn how to implement neural networks wi
 th Keras\n- Acquire skills to start deep learning projects\n\nPrerequisite
 s:\n-Basic bioinformatics knowledge\, good knowledge of Python and the Lin
 ux terminal.\n\nThis course is for bioinformaticians or other researchers 
 with some technical expertise\, who are interested in deep learning (AI) b
 ut have not yet had the opportunity to get to grips with it.\n\nWe recomme
 nd\, that you bring your own computer\, which should run Linux. Ideally it
  also has a CUDA compatible graphics card\, this is optional tough. If you
  can’t bring a suitable laptop\, please let us know during registration\
 , so we can prepare access to a computer for you.\n\nKeywords:\nLLM\, Deep
  learning\, Keras\, Tensorflow\n\nTools:\nKeras\, Tensorflow
LOCATION:Gießen
SUMMARY:Introduction to Deep Learning
URL;VALUE=URI:https://www.denbi.de/training-courses-2024/1810-introduction-
 to-deep-learning
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