LLM University
Cohere
Last updated June 30, 2026
LLM University is a free, code-along course from Cohere that teaches how large language models work and how to build with them. It runs through a sequence of modules, starting with the foundations — embeddings, attention, and the transformer architecture behind modern models — then moves into practical territory: representing and searching text by meaning, generating and steering output, engineering prompts, building retrieval-augmented systems, and giving models access to tools. The material is hands-on rather than purely theoretical, with worked examples you run yourself. It suits a developer who wants to move from a vague sense of how language models work to actually wiring one into an application.
What you'll learn
- How large language models represent words and sentences as embeddings, and how attention and transformers fit together
- Turning text into searchable meaning: semantic search, clustering, and dense retrieval
- Generating and controlling model output, including output parameters and prompt basics
- Prompt engineering: constructing and chaining prompts, then evaluating what comes back
- Retrieval-augmented generation (RAG) — grounding a model's answers in your own documents
- Giving a model tools to call so it can act, not just answer
Frequently asked questions about LLM University
Who is LLM University for?
Developers comfortable reading code who want a hands-on grounding in how large language models work and how to build retrieval- and tool-using applications with them.
Is LLM University free?
Yes — LLM University is completely free to take.
What are the prerequisites for LLM University?
Comfortable reading code; a free Cohere API key to run the examples.
Do you need to code for LLM University?
Yes — LLM University involves hands-on coding.
Why we suggest this course
A structured path from first principles through to retrieval and tool use, written for developers who learn by building rather than reading. One thing to know: several examples run on Cohere's own API, so you'll need a free API key, and the worked code naturally favors Cohere's models.