Building GenAI Apps Learning Badge Path

In this learning path, you'll build a GenAI application with MongoDB's Atlas Vector Search and learn how you can leverage it across a variety of use cases.

0:04

This learning path guides you through the foundations of building a GenAI application with MongoDB's Atlas Vector Search. You'll learn what semantic search is and how you can leverage it across a variety of use cases. Then, you'll learn how to build your own chatbot by creating a retrieval augmented generation application with MongoDB and Langchain.

To earn your badge, complete the content in this learning path and then pass the short assessment at the end. You will receive an email with your official Credly badge and digital certificate within 24 hours.


Milestones
  • Learning Badge Content


    Introduction to AI and Vector Search

    Required
    Unit
    | Parker Faucher, Katie Redmiles, Emily Pope, Vick Mena

    30 Minutes

    Learn about the foundations of AI and how Atlas Vector Search fits in.
    View Details

    Using Vector Search for Semantic Search

    Required
    Unit
    | Parker Faucher, Sarah Evans, Vick Mena, John McCambridge, Emily Pope, Harshad Dhavale

    1.75 Hours

    Learn all about Atlas Vector Search as you build a semantic search feature. Leverage both Atlas Search and Atlas Vector Search to identify the most relevant search results.
    View Details

    Using Atlas Vector Search for RAG Applications

    Required
    Unit
    | Henry Weller, Parker Faucher, Aaron Becker, Emily Pope, Daniel Curran, Manuel Fontan Garcia

    5 Hours

    Learn how to implement retrieval-augmented generation (RAG) with MongoDB in your application. Learn what retrieval augmented generation is and set it up using the MongoDB Python driver.
    View Details

    Managing Atlas Vector Search Indexes

    Required
    Unit
    | Parker Faucher

    1.5 Hours

    Learn how to manage your Atlas Vector Search indexes using the Atlas CLI and MongoDB Shell.
    View Details

    Data Ingestion for RAG Applications

    Required
    Learning Byte
    | Manuel Fontan Garcia

    20 Minutes

    Learn about the Data Ingestion Pipeline for retrieval-augmented generation (RAG) applications.
    View Details

    Building RAG Applications with LlamaIndex and MongoDB

    Elective
    Learning Byte
    | MongoDB University

    15 Minutes

    Learn to use LlamaIndex to build a RAG application powered by Atlas Vector Search.
    View Details

    MongoDB and GenAI Glossary

    Elective
    Microcourse
    | MongoDB University

    15 Minutes

    A guide to key terms and concepts used when building, deploying, and evaluating generative AI applications with MongoDB.
    View Details

  • Learning Badge Assessment


    Building GenAI Apps Learning Badge Assessment

    Required
    Assessment
    This assessment will test your knowledge of developing GenAI applications using MongoDB Atlas Vector Search as well as your understanding of semantic search and how to build chatbots with retrieval-augmented generation (RAG), MongoDB, and Langchain.
    View Details