LlamaIndex Develop LLM Powered Apps [UPDATE - 2026] (Udemy.com)
[UPDATE - 2026]) Learn LlamaIndex by building FAST a real world generative ai LLM powered application LLM (Python)
Created by: Eden Marco
Last updated March 2026
What you will learn
- Become proficient in LlamaIndex
- Have an end to end working LlamaIndex based generative AI application
- Prompt Engineering Theory: Chain of Thought, ReAct, Few Shot prompting and understand how LlamaIndex is built under the hood
- Understand how to navigate inside the LlamaIndex opensource codebase
- Large Language Models theory for software engineers
- Vectorestores/ Vector Databases (Pinecone, FAISS,)
- Retrieval Augmentation Generation (RAG)
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.6 out of 5higher than 67% of them
- Reviews5,753#98 of 1,183 by number of reviews
- Length6.4 hourslonger than 55% of them
- Last updatedMarch 2026more recently than 69% of them
Course Description
Welcome to first LlamaIndex Udemy course - Unleashing the Power of LLM!
This comprehensive course is designed to teach you how to QUICKLY harness the power the LlamaIndex library for LLM applications.
This course will equip you with the skills and knowledge necessary to develop cutting-edge LLM solutions for a diverse range of topics.
Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python
In this course, you will embark on a journey from scratch to building a real-world LLM powered application using LlamaIndex.
We are going to do so by build the main application:
Documentation Helper- Create chatbot over a python package documentation. (and over any other data you would like)
The topics covered in this course include:
LlamaIndex
Retrieval Augmentation Generation
Vectorstores (Pinecone)
Node Parers- TextSplitters
QueryEngines, ChatEngines
Streamlit (for UI)
Agents, LLM Reasoning
ReAct
Output Parsers
LLMs: Few shots prompting, Chain of Thought, ReAct prompting
Throughout the course, you will work on hands-on exercises and real-world projects to reinforce your understanding of the concepts and techniques covered. By the end of the course, you will be proficient in using LlamaIndex to create powerful, efficient, and versatile LLM applications for a wide array of usages.
This is not just a course, it's also a community. Along with lifetime access to the course, you'll get:
Dedicated 1 on 1 troubleshooting support with me
Github links with additional AI resources, FAQ, troubleshooting guides
Access to an exclusive Discord community to connect with other learners
No extra cost for continuous updates and improvements to the course
DISCLAIMERS
Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python.
I will be using Pycharm/ VSCode IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts.
Instructor Details
- 4.6 Rating
5,753 Reviews
Eden Marco
I’m a passionate Software Engineer with years of experience in back-end development and cloud architecture. I was one of the first engineers at Orca Security, where I helped shape the company’s core technology, and today I work as a GenAI Architect at Google Cloud, helping organizations design and deploy advanced generative AI and cloud-native solutions.
I’m also proud to be a LangChain Ambassador, actively contributing to the open-source community and helping developers build powerful LLM applications using the LangChain ecosystem.
I hold a Bachelor’s degree in Computer Science from the Technion, and I’ve always had a deep passion for teaching and mentorship. I taught Functional Programming and Introduction to Computer Science at Reichman University, where I guided the next generation of software engineers.
My courses are built on real-world experience and designed to give you practical, production-ready skills
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Reviews
By Anonymized User on 6/19/2026
Good and Informative.
By Anonymized User on 6/2/2026
This is not suitable for non developer ppl
By Anonymized User on 5/29/2026
Excellent Course
By Anonymized User on 4/3/2026
This is a lot of training.
By Anonymized User on 2/27/2026
Insightful course content. TQ
By Anonymized User on 2/22/2026
great learning experience
By DJ Brown on 2/21/2026
Very much enjoying this course. It bridges the gap with DeepLearning.ai
By Petro KRYVOSHAP on 2/18/2026
Очень полезный и показан на примерах
By Anonymized User on 2/6/2026
amazing course thank you
By Anonymized User on 10/28/2025
detailed explanation. interesting
Quality Score
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Overall Score : 92 / 100












