• Gießen

Educators:
Lukas Beierle, Sonja Diedrich, Dominik March (BiGi)

Date:
December 2nd and 3rd, 2024.

Location:
Justus Liebig University
Heinrich-Buff-Ring 58
35392 Gießen
Room 0024a

Contents:
The deep learning course offers a comprehensive introduction to essential concepts and practical applications.

On the first day, participants 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 preparation and encodings led by Sonja Diedrich, and hands-on sessions using TensorFlow and Keras, culminating in a real-world end-to-end example.

The second day features a guest talk by Prof. Dr. Andreas Dominik, a discussion session, and an introduction to large language models. The afternoon is dedicated to practical activities with pretrained language models and regression techniques using neural networks, finishing with an exploration of deep learning's future in bioinformatics.

This streamlined course promises to deepen your understanding of deep learning while equipping you with skills to apply these techniques in various research contexts.

Monday, 02.12.2024, morning session:
Onboarding & Introduction
• 10:00 - 10:30 → Arrival of participants
• 10:30 - 11:00 → Welcome & introduction
• 11:00 - 12:00 → Introduction to deep learning
• 12:00 - 13:00 → Lunch break

Monday, 02.12.2024, afternoon session: Deep learning basics
• 13:00 - 13:30 → History of deep learning
• 13:30 - 14:30 → Neural networks
• 14:30 - 14:45 → Short break
• 14:45 - 15:15 → Data preperation & encodings feat. Sonja Diedrich
• 15:15 - 15:45 → Tensorflow and Keras
• 15:45 - 16:30 → End-to-End example

Tuesday, 03.12.2024, morning session: Guest talk & Hands-on
• 09:00 - 09:45 → Guest talk: Prof. Dr. Andreas Dominik
• 09:45 - 10:15 → Talk discussion
• 10:15 - 10:30 → Coffe break
• 10:30 - 11:00 → Recap and hands-on infos
• 11:00 - 11:45 → Short introduction to large language models
• 11:45 - 12:45 → Lunch break

Tuesday, 03.12.2024, afternoon session: More Hands-on
• 12:45 - 14:15 → Pretrained language models hands-on
• 14:15 - 14:30 → Short break
• 14:30 - 15:30 → Regression with neural networks
• 15:30 - 15:45 → Short break
• 15:45 - 16:15 → Outlook & deep learning in bioinformatics 2

Learning goals:
- Overview of the topic deep learning (with bioinformatic examples)
- Understanding the basics of neural networks
- Know the deep learning project lifecycle
- Understand the importance of data preprocessing
- Learn how to implement neural networks with Keras
- Acquire skills to start deep learning projects

Prerequisites:
-Basic bioinformatics knowledge, good knowledge of Python and the Linux terminal.

This course is for bioinformaticians or other researchers with some technical expertise, who are interested in deep learning (AI) but have not yet had the opportunity to get to grips with it.

We recommend, 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.

Keywords:
LLM, Deep learning, Keras, Tensorflow

Tools:
Keras, Tensorflow

Contact:
This email address is being protected from spambots. You need JavaScript enabled to view it.

Registration:
This email address is being protected from spambots. You need JavaScript enabled to view it.

- The number of participants is limited to: 20
- We can not cover any travel cost and/or accomodation costs
- We provide catering during the course ‣ Lunch on the course days, coffee, drinks and snacks during the breaks
- We will use Python as programming language with the library Keras