LlamaIndex- Develop LLM powered applications with LlamaIndex
LlamaIndex- Develop LLM powered applications with LlamaIndex Course
Learn LlamaIndex by building FAST a real world generative ai LLM powered application LLM (Python)
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. I will be using Pycharm IDE but you can use any editor you’d like since we only use basic feature of the IDE like debugging and running scripts.
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.
What you’ll learn in LlamaIndex Course
- 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)
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Who this LlamaIndex course is for:
- Software Engineers that want to learn how to build Generative AI based applications with LlamaIndex
- Backend Developers that want to learn how to build Generative AI based applications with LlamaIndex
- Fullstack engineers that want to learn how to build Generative AI based applications with LlamaIndex
Taught by Eden Marco
