Courses on a specific date with a live lecturer

Term

Language

Place

Form

Price without VAT

Open term

Language

Place

Praha

Form

classroom

Code of the course: PU23110153-0001

Price without VAT

4 990 Kč

Order

Open term

Language

Place

online

Form

virtual classroom

Code of the course: PU23110153-0002

Price without VAT

4 990 Kč

Order

Course description

We will learn about transformers, the basic building blocks of modern language models, introduce the most well-known architectures, and show how large language models can be used for a variety of applications. No paid third-party account is required for the hands-on exercises. We’ll use open-source models that, when used properly, are just as good as the biggest commercial models.

Required knowledge

Basic knowledge of programing in Python
Basics of machine learning on the level of our course Introduction to machine Learning

Target audience

This course is designed for anyone who is fascinated by the capabilities of large language models (LLMs) and generative artificial intelligence, and wants to delve into the subject beyond the basic user level.

Course content

Overview of generative AI (text, images)
Evolution of language modeling
Transformers
Types of transformer-based LLMs (encoder, decoder, encoder-decoder)
Reinforcement learning with human feedback
Overview of the most popular transformer-based LLMs (BERT, GPT, LLAMA, T5, BART…)
Transformer-based classification example with HuggingFace in Google Colab
Prompt engineering: in-context learning, zero shot, one shot and few shot prompting, configuration parameters of the generative process
Practical examples of in-context learning with HuggingFace in Google Colab
Full fine-tuning of large language models, parameter-efficient fine-tuning (LoRA)
Text generative AI evaluation (ROUGE, BLEU)
Practical example of parameter efficient fine-tuning with HuggingFace in Google Colab
Retrieval Augmented Generation (RAG)

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