Course Overview
This course explores the intersection of artificial intelligence and MongoDB, equipping learners with the skills to build modern AI-powered applications. Covering vector search, retrieval-augmented generation (RAG), and AI agents, students will learn how MongoDB Atlas serves as a unified data platform for developing intelligent, scalable, and production-ready AI solutions.
Course Format
The course is formatted into seven lessons. It is recommended to go through the lessons in sequential order as the content and complexity builds as you progress. The lessons are formatted as slide decks with detailed instructor notes. They can be used as lectures during the semester, for asynchronous learning, and or/ as complementary material to self-paced learning on MongoDB University.
Skill Badges
Each lesson in this course corresponds to a Skill Badge. At the end of each lesson deck is a link to the Skill Check assessment. The Skill Check is a 10-question assessment that can be taken as many times as needed. Once passed, learners earn the corresponding Skill Badge, a free credential they can add to their resume and professional profiles.
Skill Badges validate competency in specific MongoDB topics and demonstrate commitment to professional development. We encourage both you and your students to earn these badges throughout the course.
Lesson Slides
Vector Search Fundamentals
RAG with MongoDB
AI Agents with MongoDB
AI Data Strategy with MongoDB
Vector Search Performance
Voyage AI with MongoDB
Memory for AI
The materials are freely available for non-commercial use and are licensed under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.