ExpertAdvancedAutomation and agents

RAG and knowledge bases

Build a system that answers questions from your own documents

9 lessons2h 7m71 students

4.9

What you will learn

Explain why RAG matters even with a large context window

Prepare and split documents into chunks correctly

Work with vector databases and semantic search

Combine keyword and embedding-based search

Apply reranking to improve retrieval accuracy

Evaluate a RAG system with metrics, not by eye

Add access control and update a knowledge base without downtime

About this course

An expert-level course on retrieval-augmented generation: preparing and chunking documents, vector databases, hybrid search, reranking, evaluating answer quality, and production rollout — access control, privacy, and updating a knowledge base without downtime.

Course content

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9 lessons

2h 7m

01Why RAG even with a large context window
13mFree preview
02Preparing and chunking documents
15m
03Vector databases and semantic search
15m
04Hybrid search: keywords plus embeddings
13m
05Reranking for better retrieval
12m
06Evaluating a RAG system with metrics
14m
07Access control and data privacy in RAG
13m
08Updating a knowledge base without downtime
12m
09Final project: build a knowledge assistant
20m

Requirements

Inside large language models or equivalent knowledge

Programming experience

Basic understanding of databases

$499

9 lessons
2h 7m
Lifetime access
Certificate on completion
Personal mentor

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2h 28m

4.9

$399$499