Advanced RAG: Build & Deploy Production GenAI Apps93% OFF Discount Coupon

Multi-Agent RAG, CrewAI, AutoGen, Microsoft Agent Framework, RAG, Langchain, Deep RAG, Production RAG, RAGWire

4.7 out of 5
230 students
Created by KGP Talkie | Laxmi Kant
English
Updated May 2026

Quick Facts — Course Summary

Here's a quick overview of everything you need to know about Advanced RAG: Build & Deploy Production GenAI Apps before you enroll:

Course Name: Advanced RAG: Build & Deploy Production GenAI Apps
Platform: Udemy
Instructor: KGP Talkie | Laxmi Kant
Coupon Last Verified: May 12, 2026
Level: Advanced
Topic: IT & Software
Subtopic: Retrieval Augmented Generation (RAG)
Total Time: 11h of video content
Language: English
Access Type: Unlimited lifetime access + updates
Certificate: Included upon completion from Udemy
Main Skills: Build a production RAG pipeline with BM25 hybrid search, RRF fusion, and Qdrant vector database · Build agentic RAG systems with LangChain, LangGraph self-correcting agents, and supervisor workflows · Build multi-agent RAG with CrewAI, Microsoft AutoGen, and Microsoft Agent Framework
Requirements: Basic Python programming knowledge (functions, classes, pip) · Familiarity with REST APIs and using a terminal or command line
Current Price: $9.99 (was $149.99). You save $140.00 with 93% discount.
How to Apply: Click the coupon button to activate your discount automatically
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Skills You'll Master

By the end of Advanced RAG: Build & Deploy Production GenAI Apps, you'll have these practical skills:

Build a production RAG pipeline with BM25 hybrid search, RRF fusion, and Qdrant vector database .
Build agentic RAG systems with LangChain, LangGraph self-correcting agents, and supervisor workflows .
Build multi-agent RAG with CrewAI, Microsoft AutoGen, and Microsoft Agent Framework .
Deploy RAG agents to AWS ECS Fargate, GCP Cloud Run, Azure, Railway, and Render with Docker .
Build a FastAPI backend with OpenAI-compatible endpoints, SSE streaming, and Postman testing .
Build a production Chainlit chat UI with authentication, chat history, and document ingestion .
Configure RAGWire with OpenAI GPT, Groq, Google Gemini, Ollama, and HuggingFace embeddings .
Implement LLM-driven auto metadata filtering over complex nested document structures in Qdrant.

What You Need Before Starting

Before enrolling in Advanced RAG: Build & Deploy Production GenAI Apps, make sure you have:

Basic Python programming knowledge (functions, classes, pip)
Familiarity with REST APIs and using a terminal or command line
Basic understanding of Gen AI and Langchain concepts

About This Udemy Course

The following is the full official course description for Advanced RAG: Build & Deploy Production GenAI Apps as published on Udemy by instructor KGP Talkie | Laxmi Kant:

Retrieval-Augmented Generation (RAG) is at the core of every serious AI application today. But basic RAG pipelines quickly hit their limits when documents are large, queries are complex, or your application needs to run reliably in production.

In this course, you will build RAGWire — a production-grade RAG toolkit built on LangChain, Qdrant, and LangGraph — from the ground up. You will start with a simple hybrid search pipeline and progressively add advanced retrieval, metadata filtering, agentic RAG, multi-agent frameworks, a full chat UI, and multi-cloud deployment.

By the end of this course you will know how to:
  • Build a hybrid RAG pipeline with BM25 sparse + dense retrieval and Reciprocal Rank Fusion (RRF)
  • Configure RAGWire with OpenAI GPT, Groq, Google Gemini, Ollama, and HuggingFace embeddings
  • Implement LLM-driven auto metadata filtering over complex, nested document structures
  • Build agentic RAG pipelines with LangChain agent tools, memory, and reasoning
  • Build a self-correcting RAG agent that grades its own retrieval and rewrites queries when quality is low
  • Build supervisor multi-agent systems that route queries to specialist agents using LangGraph
  • Build multi-agent document analysts with CrewAI, Microsoft AutoGen, and Microsoft Agent Framework
  • Build a production Chainlit chat UI with authentication, chat history, and document upload
  • Build a FastAPI backend with OpenAI-compatible /v1/chat/completions endpoints and SSE streaming
  • Deploy RAG agents to Render, Railway, AWS ECS Fargate, GCP Cloud Run, and Azure
  • Secure production APIs with API keys and protect credentials with Docker .dockerignore
This is a hands-on, code-first course. Every section produces working, runnable code that you can adapt to your own documents and use cases.

Compare Similar Courses

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Is the Advanced RAG: Build & Deploy Production GenAI Apps Coupon Worth It?

Expert review by Andrew Derek, Lead Course Analyst at CoursesWyn.Last updated: May 12, 2026.

Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, Advanced RAG: Build & Deploy Production GenAI Apps is a high-value resource for learners seeking to build skills inIT & Software. Taught by KGP Talkie | Laxmi Kant on Udemy, the 11h course provides a structured progression from foundational concepts to advanced techniques— making it suitable for learners at all levels. The current coupon reduces the price by 93%, from $149.99 to $9.99, removing the primary financial barrier to enrollment.

What We Like (Pros)

  • Verified 93% price reduction makes this course accessible to learners on any budget.
  • Aggregate student rating of 4.7 out of 5 indicates high learner satisfaction.
  • Strong enrollment base with over 230 students demonstrates course popularity and trust.
  • Includes an official Udemy completion certificate and lifetime access to all future content updates.

!Keep in Mind (Cons)

The following limitations should be considered before enrolling in Advanced RAG: Build & Deploy Production GenAI Apps:

  • The depth of IT & Software coverage may be challenging for absolute beginners without the listed prerequisites.
  • Lifetime access is contingent on the continued operation of the Udemy platform.
  • Hands-on projects and quizzes require additional time investment beyond video watch time.
Final Verdict: Worth It
This course offers exceptional value with current pricing

Course Rating Summary

Advanced RAG: Build & Deploy Production GenAI Apps Course holds an aggregate rating of 4.7 out of 5 based on 230 student reviews on Udemy.

4.7
★★★★★
230 Verified Ratings
5 stars
75%
4 stars
15%
3 stars
6%
2 stars
2%
1 star
2%

* Rating distribution is approximated from the aggregate score. Sourced from Udemy.

Instructor Profile

The following section provides background information on KGP Talkie | Laxmi Kant, the instructor responsible for creating and maintaining Advanced RAG: Build & Deploy Production GenAI Apps on Udemy.

Advanced RAG: Build & Deploy Production GenAI Apps is taught by KGP Talkie | Laxmi Kant, a Udemy instructor specializing in IT & Software. For the full instructor biography, professional credentials, and a complete list of their courses, visit the official instructor profile on Udemy.

Instructor Name: KGP Talkie | Laxmi Kant
Subject Area: IT & Software
Teaching Approach: Practical, project-based instruction focused on real-world application of IT & Software skills.

Frequently Asked Questions

The following questions and answers cover the most common queries about Advanced RAG: Build & Deploy Production GenAI Apps, its coupon code, pricing, and enrollment process.

About the Author

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Andrew Derek

Lead Course Analyst at CoursesWyn with 8+ years of experience evaluating online learning platforms. I've analyzed 500+ Udemy courses and helped thousands of learners choose the right courses for their career goals.

4.8/5 Rating
Trusted by 10K+ Students

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