RAG & Retrieval Systems
Build search-grounded AI that actually answers correctly
What you'll learn
About This Course
Design end-to-end retrieval-augmented systems: chunking, embeddings, hybrid search, reranking, and grounded generation. Capstone: a domain-specific knowledge assistant evaluated against a real test set.
Course Curriculum
5 weeks · 32 hours total
Requirements
- Python intermediate level
- Basic LLM API usage
- Understanding of ML fundamentals
Your Instructor
Meera Pillai
AI & Machine Learning Expert
An industry practitioner actively working in AI & Machine Learning. Brings real-world experience and production-grade examples to every session. Known for clear explanations and strong student outcomes.
Student Reviews
4.8
Course Rating
Ravi M.
2 weeks ago
Absolutely fantastic course! The instructor explains complex concepts with ease, and the hands-on projects really solidified my understanding. Already applied several techniques at work.
Sakshi T.
1 month ago
Best course I've taken on this topic. The live sessions are incredibly valuable — you can ask questions in real time and get immediate feedback. Worth every rupee!
Karthik R.
1 month ago
Very practical and well-paced. The project-based approach sets this apart from other online courses. Would appreciate a few more practice exercises, but overall excellent.
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- 📅Format
- Live cohort + recordings
- ⏱️Duration
- 32 hours total
- 📶Level
- Advanced
- 🏅Certificate
- Yes, upon completion
- 👨🏫Instructor
- Meera Pillai
Tools You'll Use
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