RAG Systems (Intermediate): Build Retrieval-Augmented Generation Apps
Build RAG applications end-to-end: document chunking, embeddings, vector search, prompting, and evaluation.
Build RAG applications end-to-end: document chunking, embeddings, vector search, prompting, and evaluation.
RAG (Retrieval-Augmented Generation) is a powerful pattern for building trustworthy LLM apps over private documents. In this course, you will build a complete RAG pipeline and learn the practical decisions that make it work well.
Estimated completion time: 7–12 hours (self-paced).
Build a RAG assistant that answers questions from your knowledge base with citations.
Intermediate Python skills (functions, classes, virtual environments)
Basic understanding of LLMs and prompting
Ability to run a small Python project locally
Build a complete RAG pipeline from scratch
Choose effective chunking and retrieval strategies
Improve answer quality with grounded prompting
Evaluate retrieval and generation for reliability
Enroll Now
Students
0
Language
English
Duration
11h 30mLevel
intermediate
Expiry period
Lifetime
Certificate
yes
Dr. Kay
English
Certificate Course
0 Students
11h 30m
92 Courses
2 Reviews