12 hrs
This practical course from Hugging Face teaches you how to fine-tune and align small language models — the core techniques powering modern AI applications. You'll go beyond theory to master instruction tuning, direct preference optimization (DPO), and model evaluation, working with real code and hands-on examples.
You're the right fit if you want to move beyond prompt engineering and build or customize your own language models — without needing massive compute budgets or pre-existing machine learning expertise.
Comfort with Python and basic machine learning concepts (what a training loop is, how losses work). You don't need to have built models before, but familiarity with PyTorch or similar frameworks helps.
As India's AI job market grows, companies building AI products — from startups in Bangalore to enterprise teams at Infosys, TCS, and Wipro — need people who can fine-tune and align models cost-effectively. Model alignment and efficient training are critical bottlenecks in Indian AI teams scaling from proof-of-concept to production, especially for vernacular and domain-specific applications.
Yes. The course materials, notebooks, and all code are completely free on GitHub. No hidden paywalls or premium tiers.
About 12 hours of focused work. If you're learning part-time, plan on 2–3 weeks at a relaxed pace, or finish it in a long weekend if you're diving deep.
This course doesn't offer an official certificate. Your real credential is the trained model and the code you'll have built — show that to employers or use it in your own projects.