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This 5 day online course was co-organised by LRZ and NVIDIA Deep Learning Institute (DLI), combined lectures about Fundamentals of Deep Learning for Single and for Multi-GPUs, Building Transformer-Based Natural Language Processing Applications and Deep Learning on LRZ systems.

Jupyter Notebook 100.00%
deep-learning gpu-acceleration high-performance-computing machine-learning natural-language-processing nvidia python transformers bert large-language-models llm transformers-models

deep-learning-week's Introduction

Course

Table of Contents

  1. Description
  2. Information
  3. Certificates

Description

This online workshop combined lectures about Fundamentals of Deep Learning for single and for Multi-GPUs, Building Transformer-Based Natural Language Processing Applications and Deep Learning on LRZ systems.

The lectures were interleaved with many demos and hands-on sessions using Jupyter Notebooks. For days 1 to 4, the exercises were done in a fully configured GPU-accelerated workstation in the AWS cloud and on day 5 the LRZ AI System resources were used.

The overall goals of this intensive course week, packed with lectures about Deep Learning and AI, were the following:

  • train and deploy deep neural networks to solve computer vision problems;
  • deep understanding about the fundamentals of machine learning for working with texts;
  • practical knowledge how to use transformer-based natural language processing models for advanced tasks involving languages (e.g., categorising documents);
  • learn how to effectively parallelize training of deep neural networks on single and Multi-GPUs;
  • understand how to leverage the LRZ AI Systems to perform all the above tasks.

This course was co-organised by LRZ and NVIDIA Deep Learning Institute (DLI). Material developed by NVIDIA was supplemented by vendor-neutral material developed by LRZ. All instructors were NVIDIA certified University Ambassadors.

Information

All necessary information, links and lesson slides for the course can be found on the course website.

The exercises and assessments can be found in this repository and are organized in their respective folders, one for each day of the course:

A detailed description of the contents covered during this course can be found on the registration website.

Certificates

The certificates for the workshop can be found below:

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