MongoDB stores data as JSON documents, which matches how modern applications think about data. This course covers CRUD, the query language, the aggregation pipeline for analytics, index design for performance, and Mongoose for Node.js applications.
This is a text-first course that links out to the best supporting material on the internet instead of trying to replace it. The goal is to make this the best course on mongodb and document database design you can find — even without producing a single minute of custom video.
This course is built by people who ship production mongodb systems for a living. It reflects how things actually work on real projects — not how the documentation describes them.
Every day has working code snippets you can paste into your editor and run right now. The emphasis is on understanding what each line does, not memorizing syntax.
Instead of shooting videos that go stale in six months, Precision AI Academy links to the definitive open-source implementations, official documentation, and the best conference talks on the topic.
Each day is designed to finish in about an hour of focused reading plus hands-on work. You can do the whole course over a week of lunch breaks. No calendar commitment, no live classes, no quizzes.
Each day stands alone. Read them in order for the full picture, or jump straight to the day that answers the question you have today.
The document model, collection design, insertOne/insertMany, findOne/find, updateOne/updateMany, deleteOne, and the difference between embedded documents and references.
Comparison operators ($eq, $gt, $in), logical operators ($and, $or, $not), element operators, regular expression queries, and projection to limit returned fields.
The aggregation framework as a data processing pipeline: $match, $group, $sort, $lookup for joins, $unwind for arrays, and $project for shaping output.
Single field, compound, multikey, and text indexes. The explain() plan, covered queries, index intersection, and the common indexing mistakes that make MongoDB slow.
MongoDB Atlas for managed cloud hosting, Atlas Search for full-text search, and Mongoose schemas, validation, middleware, and population for Node.js apps.
Instead of shooting our own videos, Precision AI Academy links to the best deep-dives already on YouTube. Watch them alongside the course. All external, all free, all from builders who ship this stuff.
CRUD, queries, aggregation, and indexes. End-to-end MongoDB from the shell to a Node.js application.
The $match, $group, $sort, $lookup stages with real-world examples. The most powerful MongoDB feature most developers underuse.
Index types, the explain() plan, and the indexing strategies that prevent slow queries at scale.
Schemas, models, validation, and population in Mongoose with a complete Express API.
The best way to understand any technology is to read the production-grade implementations that prove it works. These repositories implement patterns from every day of this course.
The database source. The query execution and aggregation framework code explains how MongoDB translates JSON operators into storage operations.
The Node.js ODM used in Day 5. The schema compilation and query builder source explains how Mongoose maps JavaScript to MongoDB.
The official Python driver for MongoDB. Used for Python-based aggregation pipeline examples.
The driver that Mongoose builds on. Understanding the native driver explains what happens when Mongoose methods execute.
MongoDB and Mongoose are the canonical Node.js database stack. This course teaches them together with the patterns used in production.
You know SQL. This course explains the MongoDB mental model, when document storage beats relational, and the joins (lookups) you don’t get for free.
MongoDB’s flexible schema lets you change your data model without migrations. This course teaches the document design patterns that make this sustainable.
The 2-day in-person Precision AI Academy bootcamp covers MongoDB and document database design hands-on. 5 U.S. cities. $1,490. 40 seats max. June–October 2026 (Thu–Fri).
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