Artificial Intelligence is rapidly evolving, driven by open-source innovation and large-scale foundation models. Hugging Face has emerged as the leading platform for discovering, training and deploying state-of-the-art AI models, enabling developers and organizations to build powerful AI solutions efficiently.

This course is designed for developers, machine learning engineers, data scientists and AI enthusiasts who want to master the Hugging Face ecosystem - from understanding models, transformers and datasets to fine-tuning, optimizing and deploying real-world AI applications using open-source tools.

You’ll learn how to leverage the Hugging Face Hub, Transformers, Datasets, Accelerate and Spaces to build scalable, efficient, and production-ready AI solutions. By the end of this course, you’ll be able to confidently work with modern open-source LLMs and deploy interactive AI applications.

What is in this course

You begin with an introduction to Hugging Face and its ecosystem, helping you understand how models, datasets and spaces work together. You’ll then move into hands-on development using core Hugging Face libraries and workflows.

Throughout the course, you’ll gain practical experience through demonstrations and projects that cover:

• Understanding Hugging Face models, datasets, and space cards

• Exploring and using pre-trained models from the Hugging Face Hub

• Working with the Transformers library for inference and customization

• Preparing and tokenizing datasets using the Datasets library

• Fine-tuning models on custom datasets

• Evaluating model performance and managing training workflows

• Optimizing training using Accelerate and Optimum libraries

• Deploying models as interactive applications using Hugging Face Spaces

• Building end-to-end AI applications with open-source models

  
  

By the end of this course, you’ll have the skills and confidence to design, train, optimize, and deploy AI solutions using the Hugging Face ecosystem.

Special Note

This course focuses heavily on hands-on learning. Modules include live demonstrations and practical workflows, ensuring you gain real-world experience with Hugging Face tools rather than just theoretical knowledge.

Course Structure

• Lectures

• Live Demonstrations

• Hands-on Labs

Course Contents

• Introduction to Hugging Face

• Hugging Face Ecosystem and Hub

• Exploring Models and Model Cards

• Transformers Library Deep Dive

• Working with Datasets

• Fine-Tuning and Training Models

• Model Evaluation and Optimization

• Scaling and Performance Optimization

• Model Deployment with Hugging Face Spaces

All sections of this course are demonstrated live, with the goal of encouraging enrolled users to set up their own environments, complete the exercises and learn through hands-on experience!