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DeepLearning.AI via Coursera

JavaScript RAG Web Apps with LlamaIndex

4.716 ratings at Coursera

Overview

Get started building full-stack RAG web applications. This course introduces the basics of Retrieval Augment Generation (RAG), including its practical implementation with JavaScript. You’ll assemble an intelligent agent capable of running its own queries. This course will guide you through the process of building a full-stack JavaScript web application, from the API server to a React component that queries your data. You’ll also learn to develop persistent chat that streams your answers to an interactive front-end in real time.

Learn from Laurie Voss, VP of developer relations at LlamaIndex, web developer and the co-founder of npm, the central registry of JavaScript packages.

In this course:

1. Learn to build a RAG application in JavaScript for querying your own data.

2. Develop tools to interact with multiple data sources using a router query engine that intelligently selects the right tool for your queries.

3. Build a full-stack web application step by step, starting with a backend web app and progressing to an interactive React frontend that calls your API to display query results.

4. Learn about production-ready techniques, including persisting your data, chatting with your data, and streaming responses for multiple queries.

5. Create a user-friendly web app that can chat with data using the create-llama command line tool from LlamaIndex.

Start building RAG web applications in JavaScript that allow you to interact with your data using LlamaIndex.

Syllabus 1

  1. JavaScript RAG Web Apps with LlamaIndex 1.5 hours

    Get started building full-stack RAG web applications. This course introduces the basics of Retrieval Augment Generation (RAG), including its practical implementation with JavaScript. You’ll assemble an intelligent agent capable of running its own queries. This course will guide you through the proc…

Advantages and disadvantages

Advantages

  • Structured courses with graded quizzes, assignments and deadlines you can reset.
  • A shareable certificate from the university or company when you pay.
  • Financial aid is often approved for students in India (apply 15 days before you need it).
  • Andrew Ng and his team are among the clearest AI teachers anywhere.
  • Short courses are made with the companies building the tools (OpenAI, Google, AWS, Hugging Face).
  • From DeepLearning.AI, a well-regarded name.
  • Self-paced: start any time.
  • A clear syllabus (1 parts) you can see before you start.

Disadvantages

  • Paid after a 7-day free trial (Coursera Plus or per course).
  • Some courses can be audited for free, but graded work and certificates need payment.
  • Short courses are 1–2 hours: an introduction, not mastery.
  • Some notebooks need a paid Pro plan or your own API key.
  • Short (1 hour): an overview, not deep coverage.

Some points apply to every course of this kind; see how we rank.

This course is paid. Here is how to take it for free

  • Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
  • Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.

Taught by

  • Laurie VossVP of Developer Relations, LlamaIndex

DeepLearning.AI is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (90/100). Andrew Ng's courses.

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