• views: 88
• date: 24 December 2025
• posted by: voska89

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 courseYou 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 cardsExploring and using pre-trained models from the Hugging Face HubWorking with the Transformers library for inference and customizationPreparing and tokenizing datasets using the Datasets libraryFine-tuning models on custom datasetsEvaluating model performance and managing training workflowsOptimizing training using Accelerate and Optimum librariesDeploying models as interactive applications using Hugging Face SpacesBuilding end-to-end AI applications with open-source modelsBy 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 NoteThis 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 StructureLecturesLive DemonstrationsHands-on LabsCourse ContentsIntroduction to Hugging FaceHugging Face Ecosystem and HubExploring Models and Model CardsTransformers Library Deep DiveWorking with DatasetsFine-Tuning and Training ModelsModel Evaluation and OptimizationScaling and Performance OptimizationModel Deployment with Hugging Face SpacesAll 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
Homepage

https://www.udemy.com/course/build-deploy-ai-with-hugging-face-hands-on/

   
   
   

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