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LlamaIndex- Develop LLM powered applications with LlamaIndex

SynopsisLlamaIndex- Develop LLM powered applications with LlamaIndex,...
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LlamaIndex- Develop LLM powered applications with LlamaIndex, available at $84.99, has an average rating of 4.26, with 41 lectures, based on 493 reviews, and has 5623 subscribers.

You will learn about 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) This course is ideal for individuals who are Software Engineers that want to learn how to build Generative AI based applications with LlamaIndex or Backend Developers that want to learn how to build Generative AI based applications with LlamaIndex or Fullstack engineers that want to learn how to build Generative AI based applications with LlamaIndex It is particularly useful for Software Engineers that want to learn how to build Generative AI based applications with LlamaIndex or Backend Developers that want to learn how to build Generative AI based applications with LlamaIndex or Fullstack engineers that want to learn how to build Generative AI based applications with LlamaIndex.

Enroll now: LlamaIndex- Develop LLM powered applications with LlamaIndex

Summary

Title: LlamaIndex- Develop LLM powered applications with LlamaIndex

Price: $84.99

Average Rating: 4.26

Number of Lectures: 41

Number of Published Lectures: 41

Number of Curriculum Items: 41

Number of Published Curriculum Objects: 41

Original Price: $199.99

Quality Status: approved

Status: Live

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)
  • Who Should Attend

  • 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
  • Target Audiences

  • 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
  • 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:

    1. Dedicated 1 on 1 troubleshooting support with me

    2. Github links with additional AI resources, FAQ, troubleshooting guides

    3. Access to an exclusive Discord community to connect with other learners

    4. No extra cost for continuous updates and improvements to the course

    DISCLAIMERS

    1. 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.

    Course Curriculum

    Chapter 1: Introduction

    Lecture 1: Introduction

    Lecture 2: What is Llamaindex

    Lecture 3: Courses discord server

    Chapter 2: THE GIST of LlamaIndex Get started with your hello world LlamaIndex Script

    Lecture 1: Project Setup (Pycharm)

    Lecture 2: Your First LlamaIndex Index

    Lecture 3: Quick Check In

    Chapter 3: Documentation helper

    Lecture 1: What are we building?

    Lecture 2: Retrieval Augmentation Generation (RAG) Theory: Vectorstores, Embeddings

    Lecture 3: Downloading the LlamaIndex Documentation

    Lecture 4: Setting up our development environment

    Lecture 5: LlamaIndex core abstractions: Pipeline imported classes

    Lecture 6: Loading and Chunkifying the LlamaIndex docs into LlamaIndex nodes

    Lecture 7: Ingestion the LlamaIndex nodes in Pinecone vectorstore

    Lecture 8: QueryEngine & Retrieval Augmentation with LlamaIndex

    Lecture 9: Streamlit Frontend

    Lecture 10: Citations and Listing source nodes

    Lecture 11: Node Post Processors- SentenceEmbeddingOptimizer, DuplicatePostProcessor

    Chapter 4: LlamaIndex Implementation- Under the hood and internals

    Lecture 1: Under the hood- Retrieval

    Lecture 2: Under the hood- Augmentation Generation

    Chapter 5: LlamaIndex ReAct Agents

    Lecture 1: Introduction to agents

    Lecture 2: Setting up agent development environment

    Lecture 3: Our First Agent – Haiku Agent

    Lecture 4: Operating System Agent

    Lecture 5: LlamaIndex ReAct internals – Under the hood

    Lecture 6: Agents In Production

    Lecture 7: LlamaIndex Function Calling Agent

    Chapter 6: Prompt Engineering Thoery

    Lecture 1: The GIST of LLMs

    Lecture 2: What is a Prompt? Composition of a formal prompt

    Lecture 3: Zero Shot Prompting

    Lecture 4: Few Shot Prompting

    Lecture 5: Chain of Thought Prompting

    Lecture 6: ReAct

    Lecture 7: Prompt Engineering Quick Tips

    Chapter 7: Troubleshooting Section

    Lecture 1: Have a technical issue? WATCH THIS FIRST. I Promise this will help!

    Lecture 2: LlamaIndex Latest- Upgrading code to

    Chapter 8: LangChain

    Lecture 1: What is LanChain + LangChain Course Coupons

    Chapter 9: Wrapping Up

    Lecture 1: LLM Application Development landscape

    Lecture 2: Finished course? Whats next!

    Chapter 10: Useful tools when developing LLM Applications

    Lecture 1: LangChain Hub – Downloads prompt from the community

    Lecture 2: TextSplitting Playground

    Lecture 3: LlamaIndex VS LangChain

    Instructors

  • LlamaIndex- Develop LLM powered applications with LlamaIndex  No.2
    Eden Marco | LLM Specialist
    Best Selling Instructor
  • Rating Distribution

  • 1 stars: 10 votes
  • 2 stars: 8 votes
  • 3 stars: 42 votes
  • 4 stars: 163 votes
  • 5 stars: 270 votes
  • Frequently Asked Questions

    How long do I have access to the course materials?

    You can view and review the lecture materials indefinitely, like an on-demand channel.

    Can I take my courses with me wherever I go?

    Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!