Instructor since 2024
Elena Petrova
AI engineer teaching prompting, LLM APIs and retrieval apps that work in practice
Sample
- Students
- 9,111
- Courses
- 3
- Instructor rating
- 4.5
- Reviews
- 22
About Elena
I build applications on top of large language models: assistants, document search and internal tools that save teams real time. I have learned most of what I teach by shipping features, watching them fail in odd ways and fixing them.
My courses are hands on and vendor neutral. We use the APIs from several model providers, compare results, and write small evaluations so you can tell whether a change helped.
I care about the unglamorous parts: cost, latency, privacy and knowing when a plain search or a simple rule is better than a model.
Courses by Elena
What students say
Ruth A.
Sample Changed how my team works
We built a shared prompt library after this course, and new colleagues get up to speed much faster.
Thomas R.
Sample Finally, LLM engineering done properly
Evals, tool limits and structured output in one course. This is what I needed to ship our first AI feature.
Kathrin B.
Sample Retrieval first is the right focus
Our RAG demo looked fine until we measured recall. This course showed us exactly where it was failing.
Hiro T.
Sample Citations check is clever
Verifying citations in code against retrieved sections caught many unsupported answers in our app.
Monica D.
Sample Practical and free
The five part prompt structure changed my results immediately. My emails need far fewer edits now.
Tariq S.
Sample Permissions handled properly
Filtering by access group inside the query was exactly the guidance our security team wanted.
Ananya B.
Sample The eval section is worth the price
We had no evaluation suite before. Now every prompt change runs through one in CI.
Ola M.
Sample Hybrid search plus reranking works
Adding keyword search and a reranker fixed most of our failures with product codes.