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Learning MongoDB

This is the repository for the LinkedIn Learning course Learning MongoDB. The full course is available from LinkedIn Learning.

Learning MongoDB Excelling in an ever-changing software development world requires true "full stack" experience. Knowledge of nonrelational databases in particular adds exciting new capabilities and features that make everyday development easier, more streamlined, and vastly more scalable. This course provides an introduction to using MongoDB, one of the most popular nonrelational databases. Discover how to create documents to store data, organize documents in collections, and write queries to read, update, and delete documents. Instructor Justin Jenkins also shows how to properly index data to increase performance in MongoDB, and then shows how MongoDB can be integrated with applications written in Python, Node.js, and PHP. In the final chapter, he covers basic server administration, including replication, sharding, security, and backups. Make sure to practice your newfound MongoDB skills using the challenge and solution sets issued along the way.

Learning objectives

  • Installing MongoDB on Windows and macOS
  • Creating documents and collections
  • Working with operators and arrays
  • Writing queries to update and delete data
  • Creating basic indexes
  • Coding with MongoDB and PHP, Node.js, and PHP
  • Maintaining MongoDB
  • Implementing security
  • Backing up and restoring MongoDB

MongoDB Version

This course was recorded with MongoDB version 4.2 While 4.4 will generally work for this course, unfortunately MongoDB now has broken out tools like mongoimport into a separate download which you can get here and copy into the bin directory:

Download MongoDB Database Tools (if using 4.4+)

To make sure you have tools like mongoimport and mongoexport you may need to download the MongoDB Database Tools.

https://www.mongodb.com/try/download/database-tools

Instructor

Justin Jenkins

Full Stack Developer

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Learning MongoDB

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  • JavaScript 25.7%
  • Go 24.4%
  • PHP 23.4%
  • Python 14.9%
  • Hack 11.6%