Build & Deploy AI with Hugging Face | Hands-On
Published 12/2025
Duration: 3h 1m | .MP4 1920x1080 30fps(r) | AAC, 44100Hz, 2ch | 1.69 GB
Genre: eLearning | Language: English
Learn to Build, Fine-Tune and Deploy Modern AI Models with Hugging Face
What you'll learn
- Understand the Hugging Face ecosystem and core components
- Use pre-trained models with the Transformers library
- Work with tokenizers, configs and inference pipelines
- Prepare and manage datasets using the Datasets library
- Build own model with custom config
- Fine-tune models on custom datasets
- Evaluate model performance and metrics
- Optimize and scale training with Accelerate and Optimum
- Manage and share assets on the Hugging Face Hub
- Deploy models using Hugging Face Spaces
Requirements
- Basic understanding of Python
- Familiarity with Machine Learning and Generative AI fundamentals
Description
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!
Who this course is for:
- Developers working with AI and Generative AI
- Machine Learning and NLP Engineers
- Data Scientists exploring open-source LLMs
- Students and professionals learning modern AI workflows
- Researchers and AI enthusiasts interested in Hugging Face
- Teams building and deploying AI-powered applications using open-source models
More Info
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