This is an on-site course at LRZ in Garching near Munich. There will be no possibility to join online remotely via video conference.
Participants are expected to bring their own laptops running the latest version of Chrome or Firefox. There are no PCs installed in the course room!
Contents
Applications for natural language processing (NLP) and generative AI have exploded in the past decade.
With the proliferation of applications like chatbots and intelligent virtual assistants, organisations are infusing their businesses with more interactive human-machine experiences. Understanding how transformer-based large language models (LLMs) can be used to manipulate, analyse, and generate text-based data is essential.
Modern pretrained LLMs can encapsulate the nuance, context, and sophistication of language, just as humans do. When fine-tuned and deployed correctly, developers can use these LLMs to build powerful NLP applications that provide natural and seamless human-computer interactions within chatbots, AI voice agents, and more.
Transformer-based LLMs, such as Bidirectional Encoder Representations from Transformers (BERT), have revolutionised NLP by offering accuracy comparable to human baselines on benchmarks like SQuAD for question answering, entity recognition, intent recognition, sentiment analysis, and more.
The course is part of a training series co-organised by LRZ and NVIDIA Deep Learning Institute (DLI). All instructors are NVIDIA certified University Ambassadors.
Learning Objectives
- How transformers are used as the basic building blocks of modern LLMs for NLP applications
- How self-supervision improves upon the transformer architecture in BERT, Megatron, and other LLM variants for superior NLP results
- How to leverage pretrained, modern LLM models to solve multiple NLP tasks such as text classification, named-entity recognition (NER), and question answering
- Leverage pre-trained, modern NLP models to solve multiple tasks such as text classification, NER, and question answering
- Manage inference challenges and deploy refined models for live applications
Important information
After you are accepted, please create an account under courses.nvidia.com/join.
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NVIDIA Deep Learning Institute
The NVIDIA Deep Learning Institute delivers hands-on training for developers, data scientists, and engineers. The program is designed to help you get started with training, optimising, and deploying neural networks to solve real-world problems across diverse industries such as self-driving cars, healthcare, online services, and robotics.
Prerequisites
- Experience with Python coding and use of library functions and parameters
- Fundamental understanding of a deep learning framework such as TensorFlow, PyTorch, or Keras
- Basic understanding of neural networks
Hands-On
The lectures are interleaved with many hands-on sessions using Jupyter Notebooks. The exercises will be done on a fully configured GPU-accelerated workstation in the cloud.
Language
English
Lecturers
PD Dr. Juan Durillo Barrionuevo (LRZ, NVIDIA certified University Ambassador)
Prices and Eligibility
The course is open and free of charge for people from academia from the Member States of the European Union (EU) and Associated Countries to the Horizon 2020 programme.
Registration
Please register with your official e-mail address to prove your affiliation.
Withdrawal Policy
See Withdrawal
Legal Notices
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