Retrieval and RAG
Retrieval-Augmented Generation Systems
Explore retrieval-augmented generation, including advanced retrieval techniques and hands-on query expansion.
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Course topics
Retrieval and RAG
- Query expansion
- Re-ranking
- Dense retrieval
You check the sources
Find your fit
Is this a useful starting point?
For learners with Python proficiency and basic AI and natural-language-processing knowledge.
- Starting point
- Intermediate
- Course length
- 3.5 total hours
- Lessons
- 39 lectures
Course by Paulo Dichone | Software Engineer, AWS Cloud Practitioner & Instructor
Course last updated: 05/2026
Requirements
- Basic Understanding of AI and NLP Concepts: Familiarity with foundational AI and NLP principles.
- Programming Experience: Proficiency in Python, as it will be the primary programming language used.
What is included
- 3 hours on-demand video
- 3 articles
- 1 downloadable resource
- Access on mobile
- Certificate of completion
DoJo membership: A$250 per month per seat, excluding GST. Includes fortnightly group support and a private member community.
Explore the lessons
Course curriculum.
9 sections • 39 lectures • 3h 16m total length
Introduction3 lectures • 4min
- Introduction01:54
- Course Structure00:49
- Development Environment Setup01:23
Download Code and Resources2 lectures • 2min
- PLEASE Watch this - How To Get the Source Code02:16
- Download Course Resources00:01
RAG (Retrieval-Augmented Generation) Deep Dive - Naive RAG vs Advanced RAG5 lectures • 28min
- Introduction to RAG and the RAG Triad - Overview03:03
- What is RAG and Naive RAG Overview and Pitfalls08:50
- Deep Dive into Each Naive RAG Drawbacks06:11
- Long Context vs RAG - When to Choose Each [NEW]09:17
- Check in00:56
Advance RAG Deep Dive - Advanced Techniques7 lectures • 29min
- Advanced RAG Techniques - Intro to Expansion with Generated Answers05:58
- Hands-on - Expansion with Answers - Splitting Text05:08
- Embedding the Chunks and Showing Them03:03
- Adding Documents to the Vector Store and Performing Similarity Search02:53
- Generating the Answer & Concatenating the Relevant Documents05:16
- Plotting and Projecting the Embedded Results on Graph05:24
- Query Expansion with Generated Answers - Summary01:30
Hands-on: Advanced RAG Technique - Query Expansion with Multiple Queries5 lectures • 18min
- Query Expansion with Multiple Queries - Overview03:05
- Getting Generated Augmented Queries05:38
- Retrieving and Plotting Embeddings in a 2D Graph07:01
- CHALLENGE: Your Turn00:34
- Expansion with Multiple Queries Downsides & Summary01:23
Hands-on - Advances RAG Technique: Re-Ranking with Cross-encoder4 lectures • 18min
- Re-ranking & Cross-encoder and Bi-encoders - Overview04:50
- Ranking Long-tail Results with Cross-encoder07:24
- Final Step - Pass the Ranked Documents through a LLM to Get Relevant Answer04:53
- Re-ranking Summary00:57
Hands-on - Advances RAG Technique: Dense Passage Retrieval DPR3 lectures • 8min
- Dense Passage Retrieval Overview02:14
- The DPR technique - Full Hands-on04:50
- DPR Summary00:58
Other Advanced RAG Techniques - NEW Content8 lectures • 1hr 24min
- Other Techniques01:18
- Get the Source Code for This Section00:04
- Contextual Retrieval (Anthropic's Techinique)09:56
- Late Chunking for Better Context14:18
- Agentic RAG with LangGraph24:54
- GraphRAG for Complex Reasoning19:20
- Multimodal RAG with ColPali10:29
- Advanced RAG - Summary04:04
Wrap up - What's Next2 lectures • 4min
- What's Next02:04
- Bonus Lecture01:55
From learning to practice
Try this next.
Compare two retrieval techniques on sample documents and inspect which sources they return.
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