RAG Tutorial 2026 #1: Complete Introduction to Retrieval Augmented Generation — Transcript

Full transcript

1. 0:00Hello guys. Welcome to the complete rag
2. 0:02course for beginners. I'm Harish Neel
3. 0:05and I'm the founder of openslate.ai,
4. 0:08an enterprise rag platform that
5. 0:10processes millions of documents for
6. 0:12companies all over the world.
7. 0:14And here is what I've learned about
8. 0:16building production rag systems for the
9. 0:18last 3 years.
10. 0:19So if you want to land those six-figure
11. 0:21AI engineering roles, rag isn't just a
12. 0:24nice-to-have. In fact, it is absolutely
13. 0:27essential. So here is the problem that
14. 0:29most developers face.
15. 0:30You know LangChain, you can build basic
16. 0:32chatbots, but when it comes to retrieval
17. 0:35augmented generation, you are stuck.
18. 0:38You don't really understand embeddings
19. 0:40deeply enough, your retrieval is
20. 0:42inconsistent, your chunking strategies
21. 0:45are basic, and frankly you can't build
22. 0:47the kind of production-ready rag systems
23. 0:49that enterprise companies actually pay a
24. 0:51lot of money for.
25. 0:53So that is exactly what this video
26. 0:55series is going to fix. By the end of
27. 0:57this course, you are going to master
28. 0:59every single component of rag from the
29. 1:01fundamentals like, you know, what is
30. 1:03rag, what is vector databases, all the
31. 1:06way to advanced concepts like chunking,
32. 1:09multi-query hybrid search, and
33. 1:11multi-model rag that even can process
34. 1:14tables and images. And because I want
35. 1:16you to start building immediately, I've
36. 1:18made all the source code completely free
37. 1:20and available in the GitHub repository
38. 1:22linked below. Now let me show you
39. 1:24exactly what we're going to cover in
40. 1:26this playlist. So we're going to start
41. 1:28with rag fundamentals to build your
42. 1:30foundation. Then we're going to
43. 1:32implement a complete ingestion and
44. 1:34retrieval pipeline from scratch. And
45. 1:37then we will do a deep dive into
46. 1:39chunking strategies because poor
47. 1:41chunking is the number one reason why
48. 1:43rag systems fail in production.
49. 1:45We will also explore the different types
50. 1:47of retrieval methods including
51. 1:48multi-query retrieval and reciprocal
52. 1:51rank fusion.
53. 1:52And then we will wrap it up with hybrid
54. 1:54search and rerankers. This is a
55. 1:57technique that separates amateur rag
56. 1:59implementations from enterprise-grade
57. 2:01systems.
58. 2:02Each video builds on the previous one,
59. 2:05so you will develop a complete
60. 2:07professional understanding of rag that
61. 2:09you can immediately start applying to
62. 2:11real-world projects.
63. 2:13So, if you're serious about mastering
64. 2:15rag and advancing your AI engineering
65. 2:18career,
66. 2:19hit that subscribe button because right
67. 2:20now we have many more videos packed with
68. 2:23practical implementations coming your
69. 2:25way.
70. 2:26And if you see value from the series,
71. 2:28hit that like button as well because
72. 2:30that is going to help us reach a lot
73. 2:32more developers just like you.
74. 2:35All right. So, let's dive deep into
75. 2:37video number two, where we're going to
76. 2:39be starting with questions like, you
77. 2:40know, what even is rag? So, I will see
78. 2:42you in the next video.