Course info
Jun 23, 2020
1h 51m

MongoDB is amazing! It is fast, reliable, highly scalable and flexible; and at the core of its flexibility, there is the Aggregation Framework. In this course, Aggregating Data across Documents in MongoDB, you will learn all the ways in which one find data throughout many documents. First, you will learn the Aggregation Framework in MongoDB, comparing it to Map Reduce and understanding the $match and $project stages. Next, you will discover about grouping our results and how to handle arrays with $unwind. Finally, you will explore how to save advanced reports on multiple types of aggregations. When you've finished this course, you will have foundational knowledge of the aggregation pipelines in MongoDB that will help you make the most complex operation seem incredibly easy!

About the author
About the author

Axel Sirota has a Masters degree in Mathematics with a deep interest in Deep Learning and Machine Learning Operations. After researching in Probability, Statistics and Machine Learning optimization, he is currently working at JAMPP as a Machine Learning Research Engineer leveraging customer data for making accurate predictions at Real Time Bidding.

More from the author
Interpreting Data with Statistical Models
2h 48m
Sep 28, 2020
Handling Streaming Data with Apache Pulsar
2h 7m
Sep 9, 2020
More courses by Axel Sirota
Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
[Autogenerated] Hi, everyone. My name is Access Sirota. Welcome to my course. Aggregating that across documents with Mongo db I am a machine learning engineer at Ace Up ml fanatic python overtime lover. And I am very excited to present this to you. Mongo db is amazing. It is fast, reliable, highly scalable. I'm flexible on at the core off its flexibility. There is the aggregation framework. Segregation framework is a set off analytic tools within manga TV that allow you to do analytics on documents. In one or more collections, our journey begins introducing Negra Gatien framework in Mangala Devi, comparing it to mob reviews on understanding the match on project stages to start on the note ground. Next we learn about grouping our results on how to handle arise with our wind only to go deep time into managing in America. Finally, we will explore how to save as bans reports on multiple types of aggregations with facet packet and emerge. When you have finished this course, you will have a foundational knowledge off the aggregation Pibe Lynsey manga TV that will help you make the most complex operation seem incredibly easy. I hope you'll join me in this journey to learn how to make aggregations with segregating that across documents with manga. The Vickers at your inside