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Hands-on AI and data courses built around the datasets and models on the hub — plus the courses from other providers that people most often recommend.
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How LLM agents call tools in a loop, how to design tools they use well, and how to keep agents safe and reliable.
How LLMs work, how to write prompts that get reliable results, and how to check what comes back.
A realistic account of the capabilities, with the failure mode for each.
From a promising demo to something you can operate: scope, evaluation, interface and rollout.
Build test sets, grade outputs with code, people and model-based graders, and catch regressions before your users do.
Turn text into vectors, build a semantic search index, and ground an LLM's answers in your own documents.
Hugging Face's free course on large language models and NLP with the Transformers, Datasets and Tokenizers libraries.
A free course on building AI agents: tools, reasoning loops, frameworks and evaluation.
Andrew Ng on how generative AI works, what it's good for, and how to use it in work and business.