Master MongoDB.
From your first find()
to sharded production clusters.
Twenty-plus courses — self-paced, or live instructor-led cohorts — covering the document model, aggregation, indexing, Atlas, sharding, security and Vector Search. Taught by engineers who've operated MongoDB at scale.
// find the top spenders per region, last 30d db.orders.aggregate([ { $match: { status: "paid", createdAt: { $gte: ISODate("2026-06-23") } }} , { $group: { _id: { region: "$region", customer: "$customerId" }, total: { $sum: "$amountEur" } }}, { $sort: { total: -1 } }}, { $group: { _id: "$_id.region", top: { $push: "$$ROOT" } }} , { $project: { region: "$_id", top: { $slice: ["$top", 5] } }} ]) // ~ 180ms · IXSCAN {region:1, createdAt:-1}
The parts of MongoDB that actually matter in production.
Not a "getting started" tour. Aggregation pipelines you can maintain, indexes that earn their keep, schemas that hold up under real access patterns, Atlas that stays boring, and Vector Search for real RAG.
- Aggregation pipelines end to end ($match, $group, $lookup, $facet, $setWindowFields)
- Schema and data modeling for the document world
- Indexing, ESR and reading explain() plans without guessing
- Atlas in production — networking, backups, PITR, alerting
- Replica sets, sharding, shard-key design, resharding
- Atlas Search & Vector Search for hybrid retrieval
- Security: x.509, KMS, field-level encryption, audit logs
- Node.js and Python integration patterns that survive load
- Change streams, Kafka Connect, and Spark for data platforms
Start where your pain is.
The Aggregation Framework, End to End
Compose aggregation pipelines that are readable, correct, and cheap to run.
Indexing & Query Performance
Read explain() plans without guessing and pick indexes that actually earn their keep.
Atlas Search & Vector Search for AI Apps
Build hybrid retrieval on Atlas — lexical, vector and re-ranking — for real RAG apps.
Replica Sets, Sharding & Horizontal Scaling
Design and operate sharded clusters that scale predictably.
Three tracks. Pick the one that matches your job.
Ship features on MongoDB without regret
CRUD, queries, schema, aggregation, Node.js/Python integration. For engineers building product on top of MongoDB.
- $mongodb-fundamentals
- $schema-and-data-modeling
- $aggregation-framework
Keep MongoDB predictable in production
Atlas operations, indexing, replica sets, sharding, security and performance tuning. For SREs and DBAs owning uptime.
- $mongodb-atlas-in-production
- $replica-sets-sharding
- $performance-tuning-diagnostics
MongoDB as a data & retrieval platform
Aggregation for analytics, Kafka/Spark integration, Atlas Search and Vector Search for RAG. For data and AI engineers.
- $mongodb-for-data-engineers
- $atlas-search-vector-search
Engineers who ran the on-call pager, not curriculum designers.
Every course is written by someone who's shipped, scaled or broken MongoDB in anger. We're picky about who teaches — five instructors covering ops, integration, aggregation, security and AI.
Meet the instructorsRan the on-call rotation for a 400-node Atlas fleet. Talks at re:Invent and MongoDB World.
Shipped Mongoose and Motor at production scale for six years.
Moves ~40 TB/day through MongoDB, Kafka and Spark.
"Cut our nightly aggregation from 4.2s to 180ms after the indexing course. My team's PR reviews are also better because we now speak the same explain() language."
"The schema modeling course changed how I review new services. We stopped copying SQL habits into MongoDB and it shows in the incident graphs."
"The Vector Search course is the first honest RAG content I've seen. Hybrid search + evals, not just cosine similarity screenshots."
"Passed the Developer and DBA associate exams two weeks after the bootcamp. The timed mocks are what did it."
"We rebuilt our CDC pipeline using the patterns from the Data Engineers course. Fewer moving parts, half the ops load."
"Saved us weeks in SOC2 audit prep. Sara knows exactly which evidence auditors ask for."
Short answers.
- Are the courses up to date with MongoDB 7.x?
- Yes. Every course targets 7.x, uses current Atlas UI and calls out where behaviour changed from 6.x.
- Do I need to know anything before starting?
- For most courses, comfort with JavaScript or Python and a terminal. Advanced tracks assume production MongoDB experience.
- Self-paced or instructor-led?
- Both. Self-paced courses are lifetime access from €39. Live instructor-led cohorts are dated, small (12–20 seats) and run 1–5 days with the instructor on camera.
- Are there any subscriptions?
- No. Every course is a one-time purchase in EUR. You buy what you want, when you want it.
- Do you offer team licenses?
- Yes. Instructor-led cohorts and self-paced seats can be invoiced for teams, with a real onboarding call.
- Is there a refund policy?
- 30 days on self-paced. Instructor-led cohorts refund in full up to 14 days before the start date.
Stop guessing at MongoDB.
Twenty-plus courses, three learning paths, self-paced or live. Written by engineers who've done the on-call.