In this course, you will learn how to build Retrieval-Augmented Generation (RAG) applications using LlamaIndex and JavaScript. Starting with an introduction to the course structure and prerequisites, you’ll dive straight into hands-on learning to build production-ready apps. By the end of the course, you will be able to integrate various data sources, set up an OpenAI account, and use powerful tools such as the RouterQueryEngine to handle advanced queries.
Developing RAG Apps with LlamaIndex and JS
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
5 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
What you'll learn
Master the setup and implementation of Retrieval-Augmented Generation (RAG) systems using LlamaIndex.
Gain hands-on experience creating and querying custom RAG systems with diverse data sources.
Learn how to build a full-stack chatbot app with NextJS, integrating LlamaIndex for advanced querying.
Understand production-ready techniques for deploying and maintaining your RAG applications.
Details to know
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May 2025
Assessments
7 assignments
Taught in English
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There are 8 modules in this course
In this module, we will introduce the course, discuss the prerequisites, outline the structure, and preview the exciting projects you’ll be building. You’ll gain an overview of the course and an understanding of the learning path ahead.
What's included
4 videos1 reading
In this module, we will guide you through the setup of your development environment, focusing on NodeJS installation and OpenAI API key configuration. This foundation will prepare you for the hands-on work ahead.
What's included
2 videos1 assignment
In this module, we will take a deep dive into LlamaIndex, focusing on its key features and functionality. You'll learn the core workflow and set up your first simple RAG system using LlamaIndex.
What's included
6 videos1 assignment
In this module, we will cover the main concepts behind LlamaIndex and demonstrate how to build custom RAG systems, work with structured data, and query PDFs. You’ll also create an Express API to interact with your system.
What's included
8 videos1 assignment
In this module, we will explore advanced querying techniques, including the RouterQueryEngine and how to handle multiple data sources. You’ll build more complex systems and query tools for sophisticated interactions with your RAG systems.
What's included
4 videos1 assignment
In this module, we will focus on ensuring your RAG system is production-ready. You’ll learn how to manage persistent data and apply advanced techniques to optimize system performance.
What's included
4 videos1 assignment
In this module, we will walk through building a full-stack chatbot app using NextJS, customizing it with your own data, and deploying it to Vercel for production use. You’ll learn to streamline the process with the create-llama CLI command.
What's included
4 videos1 assignment
In this final module, we will review everything you've learned, reinforce your progress, and provide guidance on how to continue your development in the field. You'll leave with a solid foundation and next steps for further growth.
What's included
1 video1 assignment
Instructor
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
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Financial aid available,