MongoDB 4.0 : MongoDB Developer & Admin Course

Course Curriculum

Chapter 1: Module 0

Lecture 1: Introduction to MongoDB Developer and Admin Course

Lecture 2: What is JSON

Lecture 3: 0.2 JSON Syntax Rules

Lecture 4: 0.3 JSON Datatypes

Lecture 5: 0.4 Example of JSON

Lecture 6: 0.5 What is BSON

Chapter 2: Module 1

Lecture 1: 1.1 Introduction to the Course

Lecture 2: 1.2 Introduction to NoSQL

Lecture 3: 1.3 Introduction to MongoDB

Lecture 4: 1.4 Features of MongoDB

Lecture 5: 1.5 Advantages of MongoDB

Lecture 6: 1.6 MySQL vs MongoDB

Lecture 7: 1.7 Cassandra vs MongoDB

Lecture 8: 1.8 CouchDB vs. MongoDB

Lecture 9: 1.9 Redis vs MongoDB

Lecture 10: 1.10 Why and When to use MongoDB

Chapter 3: Module 2

Lecture 1: 2.1 Downloading and Installing MongoDB on Windows

Lecture 2: 2.2 Configure the Mongo Shell

Lecture 3: 2.3 Access the Mongo Shell Help

Lecture 4: 2.4 Mongo Shell Quick Reference

Chapter 4: Module 3

Lecture 1: 3.1 Mapping Relational Databases to MongoDB

Lecture 2: 3.2 Datatypes in MongoDB

Lecture 3: 3.3 Database

Lecture 4: 3.4 Collection

Lecture 5: 3.5 Documents

Lecture 6: 3.6 Comparison or Sort Order

Chapter 5: Module 4

Lecture 1: 4.1 Insert Documents

Lecture 2: 4.2 Query Documents

Lecture 3: 4.2.1 Query on Embedded or Nested Documents

Lecture 4: 4.2.2 Query an Array

Lecture 5: 4.2.3 Query an Array of Embedded Documents

Lecture 6: 4.2.4 Project Fields to Return from Query

Lecture 7: 4.2.5 Query for Null or Missing Fields

Lecture 8: 4.2.6 Iterate a cursor in Mongo Shell

Lecture 9: 4.3 Update Documents

Lecture 10: 4.4 Delete Documents

Lecture 11: 4.5 Bulk Write Operations

Lecture 12: 4.6 Retryable Writes

Lecture 13: 4.7 Text Search

Lecture 14: 4.8 Geospatial Queries

Lecture 15: 4.9 Find Restaurants with Geospatial Queries

Chapter 6: Module 5

Lecture 1: 5.1 Atomicity and Transactions

Lecture 2: 5.2 Read Isolation, Consistency and Recency

Lecture 3: 5.3 Distributed Queries

Lecture 4: 5.4 Linearizable Reads via findAndModify

Lecture 5: 5.5 Query Plans

Lecture 6: 5.6 Query Optimization

Lecture 7: 5.6.1 Evaluate Performance of Current Operations

Lecture 8: 5.6.2 Optimize Query Performance

Lecture 9: 5.6.3 Write Operation Performance

Lecture 10: 5.6.4 Explain Results

Lecture 11: 5.7 Analyze Query Performance

Lecture 12: 5.8 Tailable Cursors

Chapter 7: Module 6

Lecture 1: 6.1 Aggregation Pipeline

Lecture 2: 6.1.2 Example with ZIP Code Data

Lecture 3: 6.1.3 Example with User Preference Data

Lecture 4: 6.2 Map Reduce

Lecture 5: 6.2.1 Map Reduce and Sharded Collections

Lecture 6: 6.2.2 Map Reduce Concurrency

Lecture 7: 6.2.3 Map Reduce Examples

Lecture 8: 6.2.4 Perform Incremental Map Reduce

Lecture 9: 6.2.5 Troubleshoot the Map Function

Lecture 10: 6.2.6 Troubleshoot the Reduce Function

Lecture 11: 6.3 Aggregation Commands Comparison

Lecture 12: 6.4 Variables in Aggregation Expressions

Lecture 13: 6.5 SQL to Aggregation Mapping Chart

Chapter 8: Module 7

Lecture 1: 7.1 Introduction to Data Modeling

Lecture 2: 7.2 Schema Validation

Lecture 3: 7.3 Data Model Design

Lecture 4: 7.4 Operational Factors and Data Models

Lecture 5: 7.6 Model Tree Structures

Lecture 6: 7.7 Model Data for Atomic Operations

Lecture 7: 7.8 Model Data to Support Keyword Search

Lecture 8: 7.9 Model Monetary Data

Lecture 9: 7.10 Model Time Data

Lecture 10: 7.11 Database References

Chapter 9: Module 9

Lecture 1: 9.1 Single Field Indexes

Lecture 2: 9.2 Compound Indexes

Lecture 3: 9.3 Multikey Indexes

Lecture 4: 9.3.1 Multikey Index Bounds

Lecture 5: 9.4 Text Indexes

Lecture 6: 9.4.1 Specify a Language for Text Index

Lecture 7: 9.4.2 Specify Name for text index

Lecture 8: 9.4.3 Control Search Results with Weights

Lecture 9: 9.4.4 Limit the Number of Entries Scanned

Lecture 10: 9.5 2D-sphere Indexes

Lecture 11: 9.6 2D Indexes

Lecture 12: 9.7 geoHaystack Indexes

Lecture 13: 9.8 Hashed Indexes

Lecture 14: 9.9 TTL Indexes

Lecture 15: 9.10 Unique Indexes