Master RAG: Retrieval-Augmented Generation Systems [NEW] (Udemy.com)
Unlock the Power of AI with the RAG Triad: Advanced Techniques in Information Retrieval, Response Generation with RAG
Created by: Paulo Dichone
Last updated August 2026
Our take
Based on the ratings of 6,410 students, a sample of their written reviews and the syllabus, as the course stood in August 2026. No course pays to be reviewed.
This is a short, code-along tour of advanced RAG techniques from Paulo Dichone. The syllabus shows about 3.3 hours across 39 lectures, with hands-on sections on query expansion with multiple queries, cross-encoder re-ranking and Dense Passage Retrieval, plus a longer block of newer material. Reviewers name GraphRAG, agentic RAG and multimodal retrieval there. It expects Python skills and some AI background, so it suits developers who want a map of modern RAG, not a full product build.
Students like how current it feels. One reviewer said that in August 2026 it seemed recorded an hour ago, and the course was updated that same month. Others praise the source code and the clear explanations of each concept. The complaints are few and specific. One reviewer says some packages are outdated, another that some terms go unexplained, and a third wanted more on how the code variables link together. Another found the audio hissy and the screen zoom hard to read. One calls it more walkthrough than depth, and one lone one-star review says the code is pasted from an LLM and poorly explained.
Ratings are strong: 4.5 from 6,410 reviews, with most of them four or five stars, and about 24,650 students have enrolled. At 3.3 hours it is quick to finish, which is the point. It reads best as a fast, practical survey before going deeper elsewhere. Check package versions before you start, since one reviewer found some outdated, and plan some extra reading if the terminology is new.
Pros
- Covers query expansion, cross-encoder re-ranking and DPR with hands-on code sections
- Updated in August 2026, and reviewers say it still feels fresh
- Source code is provided, and reviewers like the explanation of each concept
- Newer material touches GraphRAG, agentic RAG and multimodal retrieval
Cons
- One reviewer calls it more walkthrough than deep mastery of the topic
- One reviewer says a few packages mentioned in the course are outdated
- Audio hiss and hard-to-read screen zoom, per one reviewer
Great introductory course for building RAG systems with provided source code examples and great explanation of each concept.
Labeled intermediate. Suits people who already write Python and know basic AI terms, not total beginners.
What you will learn
- Understanding the RAG Triad:Grasp the core components: Retriever, Generator, and Fusion Module.
- Advanced Retrieval Techniques: Explore sparse and dense retrieval methods, including Dense Passage Retrieval (DPR).
- Coherent Response Generation:Generate fluent and contextually appropriate responses based on retrieved documents.
- Query Expansion and Re-Ranking Techniques:Improve document relevance through re-ranking strategies.
Course content
9 sections · 39 lectures · 3.3 hours of video 8 quizzes, 4 coding exercises, 3 articles
- 1Introduction 1 free preview3 lectures · 4 min
- 2Download Code and Resources2 lectures · 2 min
- 3RAG (Retrieval-Augmented Generation) Deep Dive - Naive RAG vs Advanced RAG 1 free preview5 lectures · 1 quiz · 28 min
- 4Advance RAG Deep Dive - Advanced Techniques 1 free preview7 lectures · 1 quiz · 29 min
- 5Hands-on: Advanced RAG Technique - Query Expansion with Multiple Queries 1 free preview5 lectures · 1 quiz · 18 min
- 6Hands-on - Advances RAG Technique: Re-Ranking with Cross-encoder4 lectures · 2 quizzes · 18 min
- 7Hands-on - Advances RAG Technique: Dense Passage Retrieval DPR3 lectures · 2 quizzes · 8 min
- 8Other Advanced RAG Techniques - NEW Content8 lectures · 1 quiz · 1.4 hours
- 9Wrap up - What's Next2 lectures · 4 min
Who it is for
The instructor says it suits
- AI Enthusiasts: Eager to explore advanced AI and NLP techniques.
- Data Scientists: Seeking to enhance their information retrieval skills.
- NLP Professionals: Aiming to master RAG systems for complex queries.
- Tech Innovators: Looking to apply cutting-edge AI in real-world applications.
What you need before you start
- 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.
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.5 out of 5higher than 45% of them
- Reviews6,410#82 of 1,183 by number of reviews
- Length3.3 hoursshorter than 68% of them
- Last updatedAugust 2026more recently than 88% of them
Course Description
Unlock the full potential of AI with our comprehensive course on Retrieval-Augmented Generation (RAG) Systems. Dive deep into the powerful RAG Triad and learn how to leverage advanced techniques in information retrieval, response generation, and agent-based architecture. Designed for AI enthusiasts, data scientists, and NLP professionals, this course provides everything you need to build state-of-the-art RAG systems that deliver accurate, contextually relevant, and coherent responses to complex queries.
What You'll Learn:
The RAG Triad: Understand the components of RAG systems, such as the retriever, generator, and Fusion Module, and how they work together to enhance information retrieval and response generation.
Advanced Retrieval Techniques: Explore sparse and dense retrieval methods, including Dense Passage Retrieval (DPR), and learn how to implement hybrid retrieval approaches for superior accuracy.
Coherent Response Generation: Master using advanced language models like GPT-3 to generate fluent and contextually appropriate responses based on retrieved documents.
Hands-On Projects: Engage in practical exercises and real-world projects to build a complete RAG system from scratch and apply your skills in various applications such as search engines, customer support, and research.
By the end of this course, you'll be equipped with the skills and knowledge to create robust RAG systems that can easily handle complex queries, making you a leader in AI.
Enroll now to transform your AI capabilities and stay ahead in the ever-evolving field of artificial intelligence.
Instructor Details
- 4.5 Rating
6,410 Reviews
Paulo Dichone
Hi, I’m Paulo – Your Guide to Mastering Development, Cloud, and AI Engineering
With a passion for empowering learners, I’ve had the privilege of teaching over 350,000 students across 175 countries. Whether you’re diving into Android, Java, Flutter, AWS Cloud, or venturing into the world of AI engineering, I’m here to help you unlock your full potential.
My Expertise
I bring extensive hands-on experience in:
AI Engineering
Mobile App Development (Android & iOS)
Cross-Platform Development (Flutter, Dart, and JavaFX)
AWS Cloud Solutions
And now, I’m also focused on the AI engineering landscape, helping developers leverage the power of machine learning and automation in their projects.
My Mission
No matter where you are in your journey—whether you're just starting or looking to sharpen advanced skills—my courses are designed to make you an exceptional developer and AWS Cloud Practitioner, equipped to tackle real-world challenges. Beyond coding, I enjoy spending time with my growing family, playing the guitar and mandolin, and traveling whenever I get the chance.
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Reviews
By Md Meraj on 8/29/2026
Amazing course and exceeded my expectations. The content was well-structured, easy to follow, and covered both foundational and advanced RAG concepts in a very practical way. I particularly enjoyed the hands-on labs covering Retrieval-Augmented Generation, Query Expansion, DPR, Contextual Retrieval, GraphRAG, Agentic RAG, and multimodal retrieval techniques.
By Anastasiya Barska on 8/18/2026
Thank you for creating this course and for keeping it up to date, as of Aug 2026 it feels like if it were recorded just an hour ago, super fresh and useful in this rapidly changing world.
By Satyajit Chainy on 8/15/2026
An excellent course for developing a solid understanding of Retrieval-Augmented Generation (RAG). The material is rich with insights, and I found that going through it more than once helped reinforce and deepen my understanding of the concepts. Thank you for creating such a high-quality learning experience. I sincerely appreciate the time, effort, and knowledge you invested in this course.
By Sudha Chellappan on 7/28/2026
I currently write weekly project status updates manually. Text generation AI could help by drafting the update based on bullet points I provide. The AI-assisted version would look like this:
By Gajanan Hunagund on 7/3/2026
Nice, Need more explanation on code variable how to link them and call in specific area
By Erik Kato Ipsen on 6/6/2026
Great introductory course for building RAG systems with provided source code examples and great explanation of each concept.
By Anonymized User on 6/3/2026
It covers well advance topics on RAG. I feel audio is not that clear, it has mouth air sound (fiss). It is too much zoom which is not readable properly.
By Anonymized User on 5/5/2026
I learned a lot about how RAG systems can increase my capacity at work and allow me to deliver more results in less time for repetitive tasks while I focus on more value generating activities.
By Andrés Zuñiga Garzón on 1/30/2026
Explica con calma y suficiente contexto teórico que lleva a una comprensión más sencilla al momento de poner el práctica lo enseñado.
By Daniel Emenike on 1/18/2026
I was honestly expecting deep mastery or explanations into the topic. It seemed more of a walk through than an indepth knowledge. Good course regardless
Quality Score
No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.
Overall Score : 90 / 100


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