- Promoted by: Anonymous
- Platform: Udemy
- Category: IT Certifications
- Language: English
- Instructor: Pramod Kumar Singh
- Duration: 1 hour(s) 30 minute(s)
- Student(s): 460
- Rate 5 Of 5 From 0 Votes
- Expires on: 2025/12/19
-
Price:
19.990
Master the Foundations of Retrieval-Augmented Generation (RAG) to Build Smarter, Context-Aware AI Applications
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for the "Fundamentals of RAG(Retrieval Augmented Generation)" course by Pramod Kumar Singh on Udemy.
This course, boasting a 5.0-star rating from 0 reviews
and with 460 enrolled students, provides comprehensive training in IT Certifications.
Spanning approximately
1 hour(s)
30 minute(s)
, this course is delivered in English
and we updated the information on December 16, 2025.
To get your free access, find the coupon code at the end of this article. Happy learning!
Unlock the Power of Generative AI with Retrieval-Augmented Generation (RAG)!
In today’s rapidly evolving AI landscape, traditional language models—no matter how large—face a common limitation: they are bound by the static nature of their training data. As the world changes and new knowledge is created every day, relying solely on pre-trained models can lead to outdated or incomplete answers.
That’s where Retrieval-Augmented Generation (RAG) comes in.
This course, Fundamentals of RAG, is designed to help you understand and apply this cutting-edge architecture that combines the dynamic strengths of information retrieval with the generative power of large language models (LLMs). Whether you're building AI agents, chatbots, intelligent assistants, or search-enhanced applications, RAG will become a cornerstone of your solution.
We’ll start by demystifying RAG’s architecture and real-world importance:
What You’ll Learn:
Why traditional LLMs fall short when it comes to dynamic, real-time, or domain-specific information—and how RAG fills the gap
The core components of RAG: Retrieval (searching from external knowledge bases) and Generation (using LLMs to produce rich responses)
How to design, build, and deploy RAG systems from scratch using popular tools and frameworks
Hands-on projects to help reinforce learning through practical application
Hands-On Use Cases:
We’ll guide you through two real-world RAG implementations that you can apply and extend in your own projects:
LiveStockIQ – A stock market assistant that integrates with real-time financial APIs to provide current stock data, company info, and market trends. You’ll see how retrieval connects to APIs and how LLMs generate insights on top of it.
SmartRecruit – An AI-powered recruitment assistant for HR teams that intelligently analyzes resumes and matches them to job descriptions using contextual document retrieval and summarization.
Who Is This Course For?
This course is perfect for:
AI/ML engineers and data scientists looking to level up their GenAI skills
Developers building intelligent search and assistant solutions
Product managers and innovators exploring real-world applications of GenAI
Anyone curious about how LLMs can go beyond training data to create dynamic, responsive systems
By the end of this course, you won’t just understand what RAG is—you’ll be able to implement it, customize it, and integrate it into your own AI solutions.
Get ready to take your Generative AI projects to the next level with the Fundamentals of RAG!