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Developing Large Language Models

Learn to develop large language models (LLMs) with PyTorch and Hugging Face, using the latest deep learning and NLP techniques.
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Track Description

Developing Large Language Models

Start your journey to developing Large Language Models (LLMs) today! In this track, you'll learn about the latest techniques for developing state-of-the-art language models responsible for the recent boom in generative AI models, like OpenAI's GPT-4, and Meta's Llama 3. Master deep learning with PyTorch to discover how neural networks can be used to model patterns in unstructured data, such as text. Discover how the transformers architecture has revolutionized text modeling, and how to leverage the variety of pre-trained LLMs available from Hugging Face. Finally, learn about the challenges and strategies involved in building and deploying LLMs, from inception to real-world application.

Prerequisites

There are no prerequisites for this track
  • Course

    1

    Introduction to Deep Learning with PyTorch

    Learn how to build your first neural network, adjust hyperparameters, and tackle classification and regression problems in PyTorch.

  • Course

    Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.

  • Project

    bonus

    Service Desk Ticket Classification with Deep Learning

    Use deep learning to automate the classification of service desk tickets.

  • Course

    Explore the latest techniques for running the Llama LLM locally, fine-tuning it, and integrating it within your stack.

  • Course

    Learn about LLMOps from ideation to deployment, gain insights into the lifecycle and challenges, and learn how to apply these concepts to your applications.

Developing Large Language Models
6 courses
Track
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