Learn to build, deploy, and scale AI applications using Hugging Face—the platform powering over 2.5 million machine learning models used by Google, Meta, Microsoft, and thousands of organizations worldwide.
This hands-on specialization takes you from navigating the Hugging Face Hub to building multi-modal AI systems that process text, images, and audio. You'll master the Transformers library, learn to evaluate and select models for production use, fine-tune pre-trained models on custom datasets, and deploy your work to the Hub for others to use.
Through realistic role-play scenarios—including a startup investor demo and healthcare document triage system—you'll apply these skills to solve authentic industry problems. Whether you're building chatbots, content analyzers, transcription systems, or computer vision applications, this specialization provides the practical foundation you need to ship AI-powered products using open-source tools.
All projects run locally on your hardware (CPU, NVIDIA GPU, or Apple Silicon), requiring no cloud API costs—a critical skill for cost-conscious teams and privacy-sensitive applications.
Applied Learning Project
Build a complete Multi-Modal Content Analyzer as your capstone project—a production-ready system that classifies text sentiment, categorizes images, transcribes audio, and generates image captions using models you discover and evaluate on the Hugging Face Hub.
Build projects in pure Rust and learn to use the principles of Sovereign AI, creating systems that operate independently without reliance on external cloud APIs. Throughout the specialization, you'll tackle realistic role-play scenarios including: selecting models for a healthcare document triage system under compliance constraints, debugging tokenization issues in a fintech fraud detection pipeline, building cross-platform inference that works on both Mac and Windows, and preparing an AI prototype for a high-stakes investor demo.
