Course Overview
This intermediate course covers MongoDB optimization and modern application patterns. Students will learn advanced schema design patterns and anti-patterns, full-text search implementation with Atlas Search, query performance analysis and optimization, retrieval-augmented generation (RAG) with vector embeddings, and horizontal scaling through sharding. The course emphasizes practical application of optimization techniques and building AI-enabled applications with MongoDB.
Course Format
The course is formatted into six 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
Query Optimization
Advanced Schema Patterns and Anti-patterns
Atlas Search Fundamentals
Vector Search Fundamentals
RAG with MongoDB
Sharding Strategies
The materials are freely available for non-commercial use and are licensed under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.