MongoDB Aggregation Framework

MongoDB Aggregation Framework

Instructors: Nathan Leniz

Access provided by Cisco Systems

12,580 already enrolled

3 modules

Gain insight into a topic and learn the fundamentals.

66 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

66 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

36 assignments

Taught in English

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There are 3 modules in this course

This course will teach you how to perform data analysis using MongoDB's powerful Aggregation Framework.

You'll begin this course by building a foundation of essential aggregation knowledge. By understanding these features of the Aggregation Framework you will learn how to ask complex questions of your data. This will lay the groundwork for the remainder of the course where you'll dive deep and learn about schema design, relational data migrations, and machine learning with MongoDB. By the end of this course you'll understand how to best use MongoDB and its Aggregation Framework in your own data science workflow.

In this module you'll learn the fundamentals of MongoDB's Aggregation Framework. This will cover basics like filtering and sorting, as well as how to transform array data, how to group documents together, how to join data, and how to traverse graph data.

What's included

15 videos1 reading15 assignments

15 videos Total 63 minutes

Welcome! 1 minute
Course Logistics and Prerequisites 2 minutes
Aggregation Introduction 4 minutes
The Concept of Pipelines 2 minutes
Aggregation Structure and Syntax 4 minutes
$match: Filtering Documents 3 minutes
Using $project 6 minutes
Using Expressions 3 minutes
Cursor Like Methods Stages: Part 1 5 minutes
Cursor Like Methods Stages: Part 2 5 minutes
The $group Stage 6 minutes
Using Accumulator Expressions 5 minutes
$unwind 4 minutes
The $lookup Stage 4 minutes
$graphLookup Stage 6 minutes

1 reading Total 10 minutes

Setting Up Your Course Environment 10 minutes

15 assignments Total 354 minutes

Course Logistics 30 minutes
Aggregation Introduction 2 minutes
The Concept of Pipelines 30 minutes
Aggregation Structure and Syntax 30 minutes
$match: Filtering Documents 30 minutes
Using $project 30 minutes
Using Expressions 2 minutes
The $lookup Stage 30 minutes
$project and Expressions 30 minutes
Changing Document Shape with $project 20 minutes
Cursor Like Methods 20 minutes
$group Accumulators 20 minutes
$unwind and $group 30 minutes
$lookup 20 minutes
$graphLookup 30 minutes

This module is going to be focused on the different ways you can leverage MongoDB's flexible schema. You'll learn how to migrate a relational schema, how to enhance existing schemas, and how to merge datasets via an entity resolution technique.

What's included

11 videos9 assignments

11 videos Total 64 minutes

Intro to Week 2 1 minute
mongoimport 12 minutes
Importance of Schema 4 minutes
Exploring Schemas 4 minutes
Migrating Your Schema 7 minutes
Views 8 minutes
Supplementing Schemas with Accumulators 5 minutes
Tree-like Data in Individual Documents (Part 1) 4 minutes
Tree-like Data in Individual Documents (Part 2) 8 minutes
Expressive Lookup Basics 6 minutes
Entity Resolution with $lookup 6 minutes

9 assignments Total 270 minutes

Intro to Week 2 30 minutes
mongoimport 30 minutes
Importance of Schema 30 minutes
Exploring Schemas 30 minutes
Migrating Your Schema 30 minutes
Views 30 minutes
Tree-like Data in Individual Documents 30 minutes
Schemas and accumulators 30 minutes
Entity Resolution 30 minutes

This module is focused on demonstrating how MongoDB can be used in different machine learning workflows. You'll learn how to perform machine learning directly in MongoDB, how to prepare data for machine learning with MongoDB, and how to analyze data with MongoDB in preparation of doing machine learning in Python.

What's included

11 videos12 assignments

11 videos Total 68 minutes

Intro to Week 3 1 minute
Calculation of Persons-Rho 10 minutes
Intro: Associative Role Learning 11 minutes
Principal Component Analysis (Part 1) 3 minutes
Principal Component Analysis (Part 2) 7 minutes
Intro to Linear Regressions 6 minutes
Linear Regressions with MongoDB 9 minutes
Decision Trees Part 1 3 minutes
Decision Trees Part 2 11 minutes
Decision Trees Part 3 2 minutes
Intro to Clustering Algorithms 7 minutes

12 assignments Total 305 minutes

Intro to Week 3 30 minutes
Intro: Associative Role Learning 30 minutes
Principal Component Analysis 30 minutes
Intro to Linear Regressions 30 minutes
Linear Regressions with MongoDB 30 minutes
Decision Trees 30 minutes
Intro to Clustering Algorithms 30 minutes
Pearsons-Rho 15 minutes
Associative Rules on Titanic Data Set 20 minutes
Linear regression on Titanic data set 20 minutes
Decision Trees on Titanic Data Set 20 minutes
K-means usage on Titanic dataset 20 minutes

Instructors

Instructor ratings

(17 ratings)

Nathan Leniz

MongoDB Inc.

1 Course 12,580 learners

Offered by

MongoDB Inc.

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Reviewed on Sep 14, 2025

This is a great course, but more corrections on the solutions in the graded-assignment section and discussion-forum participations by the staff should be considered.

Reviewed on Sep 9, 2019

Very clear introduction to the MongoDB Aggregation Framework. Interesting and comprehensive data analysis examples as well!

Reviewed on Jul 12, 2019

The course was excellent, but there were some problems: - There were mistakes in some assignments codes. - Some codes mentioned in the lectures were not available in resources.

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