Make a model answer from your documents, and admit when it cannot.
Every organisation eventually wants the same thing: a model that answers from our documents, not from the internet. The demo takes an afternoon. The version you can put in front of a customer takes rather longer, because the failure is quiet — it retrieves the wrong passage and answers confidently anyway. Four weeks on the difference between the two, built on your own material.
- Duration
- 4 weeks · around 16 hours
- Mode
- Live online — real sessions, not recordings
- Timing
- Evenings, designed around a full-time job
- Cohort size
- 20–25
- Material
- Build on your own documents, or ours
- Recordings
- Every session recorded, yours to keep
Who this is for
- Developers asked to build a chatbot over company documents
- Teams whose first RAG attempt works in the demo and embarrasses them in production
- Data and knowledge-management people sitting on a large document estate
- Anyone who has seen a retrieval system answer fluently and wrongly
Complete beginners — this assumes you can write a script and call an API. AI Foundations covers RAG at an introductory level in week 3.
Prerequisites
- Working Python, and comfort calling an HTTP API.
No machine-learning background is required. You will not train a model in this program; you will make one useful.
Modules
4 modules · register to see what is inside each one
Why the model needs your documents at all
Covered in detail after registration
Chunking, which decides everything downstream
Covered in detail after registration
Retrieval that actually retrieves
Covered in detail after registration
Grounding, citation, refusal — and proving it works
Covered in detail after registration
What you walk away with
- A working RAG system over documents you actually care about
- An evaluation set, so “better” stops being a feeling
- Answers that carry citations, and refusals where refusal is correct
- A cost-per-query figure you can take to whoever pays for it
- Codnov Certificate of Completion, with a unique ID and a public verification link
Sample projects
- A policy and handbook assistant for an internal team
- A support assistant grounded in real product documentation
- A research assistant over a library of papers or reports, with citations
- A contract and tender search tool that quotes the clause it found
You finish with a deployed, reviewed AI project, or we re-run you free.
Requires minimum 75% attendance and on-time milestone submission. Full conditions at codnov.ai/training/terms.
Taught by Codnov engineers who build and run AI systems in production every day.
Cohort pricing is confirmed per intake — enquire for the current fee and dates. All prices exclusive of 18% GST.
Nothing is paid on this website. Register your interest and we will confirm your seat with you directly.
Register your interest
We will come back to you with the full syllabus, the schedule, and whether there is a seat in the next cohort.
Codnov Certificate of Completion. Not a degree or diploma recognised under the UGC Act, 1956 or the AICTE Act, 1987. All prices exclusive of 18% GST. Project completion guarantee subject to minimum 75% attendance and on-time milestone submission; full terms at codnov.ai/training/terms. Open to participants aged 16 and above.