While selecting the Best RAG Courses and Classes, our team considered certain factors. These were course content comprehensiveness, instructor expertise in RAG, and positive learner outcomes. We gave priority to courses that offered certificates of completion. Following such an approach made sure our recommendations were authoritative.
Key Takeaways
- Access to Best RAG Courses.
- A chance to learn from highly experienced instructors.
- Certificates available to validate your skills.
# | Course Name | University/Organization | Ratings | Duration |
1. | What is Retrieval-Augmented Generation (RAG)? | YouTube | — | — |
2. | Introduction to Retrieval Augmented Generation (RAG) | Duke University | ★★★★☆ 3.8 | 02 Hours |
3. | Building Multimodal Search and RAG | DeepLearning.AI | — | 01 Hour |
4. | Open-source LLMs: Uncensored & secure AI locally with RAG | Udemy | ★★★★★ 4.8 | 10 Hours |
5. | Knowledge Graphs for RAG | DeepLearning.AI | ★★★★★ 4.7 | 01 Hour |
6. | Building Agentic RAG with LlamaIndex | DeepLearning.AI | — | 01 Hour |
7. | JavaScript RAG Web Apps with LlamaIndex | DeepLearning.AI | — | 01 Hour |
Best + Free RAG Courses & Classes….
What is Retrieval-Augmented Generation (RAG)?
-
-
- via YouTube
-
In this video, the instructor explains all about the LLM/RAG framework. You will understand how the combination of these two can bring such big advantages.
- The reason why we chose this video is its focus on explaining all about the Large Language Models. You will understand the role of RAG in detail as well.
- This video is for those who wish to understand how the model gets its info, lending more credibility to what it generates.
Introduction to Retrieval Augmented Generation (RAG)
-
-
- Duke University via Coursera
- 02 Hours of effort required!
- ★★★★★ (11 Ratings)
-
Online Course Effectiveness Score | |||
Content | Engagement | Practice | Career Benefit |
Excellent ★★★★★ |
Excellent ★★★★★ |
Fair ★★★☆☆ |
Fair ★★★☆☆ |
In this intermediate-level course, you will be taught how to import data into Pandas. You will learn to create embeddings with SentenceTransformers.
- The best thing about this course is its focus on explaining how to build a retrieval augmented generation (RAG) system with your data.
- This course is for those who wish to learn to build an end-to-end RAG system with their own data using open-source tools for a powerful generative AI application.
Building Multimodal Search and RAG
-
-
- DeepLearning.AI via Coursera
- 01 Hour of effort required!
- Course type (Self-paced)
-
An intermediate-level course where you will learn multi modality with constructive learning. You will then learn to create modality-independent embedding for seamless any-to-any retrieval.
- The reason why we chose this course is its focus on explaining how to build multi modal RAG systems that can retrieve multi modal context. You will learn to reason over it to generate more relevant answers.
- This course is for those who wish to understand how to implement industry applications of multi modal search and build multi-vector recommended systems.
Continue with more Free RAG Courses & Classes…
Open-source LLMs: Uncensored & secure AI locally with RAG
-
-
- Arnold Oberleiter via Udemy
- 1,591+ already enrolled!
- ★★★★★ (145 Ratings)
-
Online Course Effectiveness Score | |||
Content | Engagement | Practice | Career Benefit |
Excellent ★★★★★ |
Excellent ★★★★★ |
Fair ★★★☆☆ |
Fair ★★★☆☆ |
This is a bestseller course where you will understand the differences, advantages, and disadvantages of both open-source and closed-source LLMS. You will learn what LLMs are including ChatGPT, Llama, Phi3, and more.
- The best thing about this course is its focus on explaining how to find which LLMs are available and which ones are the most suitable to use. You will learn to find the best LLMs in a step-by-step guide.
- This course is for those who wish to learn all about censored vs uncensored LLMs and understand the requirements for using open-source LLMs locally.
Knowledge Graphs for RAG
-
-
- DeepLearning.AI via Coursera
- 01 Hour of effort required!
- ★★★★★ (12 Ratings)
-
Online Course Effectiveness Score | |||
Content | Engagement | Practice | Career Benefit |
Excellent ★★★★★ |
Excellent ★★★★★ |
Good ★★★★☆ |
Good ★★★★☆ |
Are you interested in learning how to use Neo4j’s query language Cypher to not only manage but retrieve data that is stored in knowledge sports? If yes then this course is the one to take.
- The best thing about this course is its focus on explaining how to write knowledge graph queries that can find and format text data to provide more relevant context to LLMs for Retrieval Augmented Generation.
- This course is for those who wish to understand how to build a question-answering system using Neo4j and LangChain to chat with a knowledge graph of structured text documents.
Building Agentic RAG with LlamaIndex
-
-
- DeepLearning.AI via Coursera
- 01 Hour of effort required!
- Course type (Self-Paced)
-
Online Course Effectiveness Score | |||
Content | Engagement | Practice | Career Benefit |
Excellent ★★★★★ |
Excellent ★★★★★ |
Good ★★★★☆ |
Fair ★★★☆☆ |
In this highly engaging course, you will learn to build an agent that has the ability to reason over your documents and even answer complex questions.
- The reason why we chose this course is its focus on explaining how to build a router agent that can help us with Q&A and other summarization tasks. You will also learn to extend that agent and pass all arguments to that agent.
- This course is for those who wish to learn to design a research agent that can handle multi-documents and learn many ways to debug and control that agent.
JavaScript RAG Web Apps with LlamaIndex
-
-
- DeepLearning.AI via Coursera
- 01 Hour of effort required!
- Course type (Self-paced)
-
This is a very interesting course where you will learn to build a RAG application in JavaScript. You will learn to use an intelligent agent that not only discerns but selects from data sources to answer our queries.
- The best thing about this course is its focus on explaining how to build a full-stack web application with an interactive frontend component and that can interact and chat with your data. You will also understand the right way to enable data chatting.
- This course is for those who wish to discover all about persisting data and understand streaming responses with the create-llama command-line tool.