Hugging Face is an essential toolkit for any developer working with state-of-the-art Large Language Models (LLMs). This course will introduce you to the powerful tools and libraries Hugging Face offers, from out-of-the-box solutions, to custom model training and configurations.

Through engaging text and video lessons, interactive excersises and coding tutorials, you'll gain the practical skills needed to work confidently with Hugging Face.

The course is structures into several chapters, each building on the last, focusing on key aspects of the Hugging Face ecosystem. Throughout each chapter we’ll be looking at specific tools and code that can help us achieve our goals and improve your skills. 

Let's take a look at the course chapters in more detail:

1. Introduction to Hugging Face
   To get started, we'll be covering exactly what Hugging Face is and all the kinds of projects it can be used for. This will give you a firm understanding of the tools available before we get stuck in with some hands-on practicals.
   
   
2. Getting Started With Pipelines
   Pipelines allow us to work with state-of-the art models in just a few lines of code! We'll be working through some practical examples of how we can create simple pipelines using LLMs for a range of Natural Language Processing tasks.
   
   
3. Hugging Face Models
   There are a whole range of models available to us through Hugging Face. Here I'll introduce you to the Models Hub, a fantastic tool for sourcing high quality models to work with. I show you how we can load different LLMs for use in our projects.
   
   
4. Hugging Face Tokenizers
   In this section of the course I'll show you a number of different ways we can preprocess text data, preparing us for some more advanced topics when working with transformer models.
   
   
5. Fine-Tuning Models
   We will work through an in-depth case study as I walk you through an example of how to fine-tune an LLM for a specific language task. We'll also be sharing our models using Hugging Face Spaces and Gradio!
   
6. Advancing Your Knowledge
   Here I will introduce you to some of the more advanced topics of working with Hugging Face such as working with large data, managing hardware configurations and integrating with other frameworks.
   
   
7. Beyond Text: Audio and Video
   The Hugging Face suite of tools makes it easy to work with transformer models across a whole range of tasks. This section of the course will the skills we have developed in earlier chapters, and adapt to work with audio and image-based data.

If you're looking to develop your skills working with Large Language Models, or AI models in general, then this course is for you. I will provide you with the knowledge and practical skills needed to become a master through Hugging Face!