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MongoDB Training

In MongoDB, a record is referred to as a "document." A document is a basic unit of data in MongoDB and is represented as a data structure composed of key-value pairs.

Codify Certificate of Completion

Certificate of Completion

Course Duration

45 days

Online and Offline

Online and Offline


MongoDB is a popular open-source NoSQL database management system that falls under the category of document-oriented databases. It provides a flexible and scalable solution for storing and managing large volumes of unstructured or semi-structured data. MongoDB is designed to handle modern data requirements, making it well-suited for various types of applications, from small projects to enterprise-level systems.

Who Should Attend:

  • Software Developers and Engineers
  • Database Administrators
  • System Architects
  • Data Scientists and Analysts
  • Anyone interested in modern data management with MongoDB


  • Basic understanding of databases and database concepts.
  • Familiarity with JavaScript and JSON is beneficial but not required.


MongoDB Course Syllabus

Master MongoDB, the leading NoSQL database, and revolutionize the way you store and manage your data!

This comprehensive MongoDB training program equips you with the skills and knowledge to excel as a MongoDB Database Administrator (DBA). Whether you're a developer, system administrator, or aspiring data professional, this course empowers you to:

  • Build Scalable and Flexible Applications: Leverage MongoDB's NoSQL structure to create programs which can handle large datasets and evolving records models simply

  • Boost Performance and Efficiency: Experience the agility and pace of MongoDB, optimizing your database operations for real-time data access to and quicker queries.

  • Become a Data Management Expert: Learn essential administration tasks like user management, security protocols, data backup and recovery, ensuring the integrity and security of your MongoDB databases.

  • Unlock Career Opportunities: As MongoDB continues to advantage great adoption, mastering this era positions you for stimulating profession prospects inside the statistics-pushed world.


What You'll Learn in Our MongoDB DBA Training:

  • MongoDB Fundamentals: Benefit a stable information the core concepts of MongoDB, consisting of information modeling, Document structure, and querying fundamentals.

  • Installation and Configuration: Learn how to install and configure MongoDB on different operating systems, manage user access, and implement robust security measures.

  • Data Management Mastery: Explore techniques for creating, managing, and querying databases and collections within MongoDB.

  • CRUD Operations in Action: perform Create, Read, update, and Delete (CRUD) operations correctly using MongoDB's question language.

  • Indexing for Performance: grasp indexing techniques to optimize facts retrieval speeds and ensure efficient question execution.

  • Backup and Recovery: Implement powerful statistics backup techniques and learn how to recover facts in case of unexpected circumstances.

  • Security and Access Control: Configure user authentication, authorization, and role-based access control (RBAC) to safeguard your MongoDB data

  • Replication and Sharding: explore advanced techniques like replication for high availability and sharding for horizontal scaling to deal with large information volumes.

  • MongoDB management tools: utilize effective equipment like MongoDB Compass and the mongo shell to streamline database administration obligations.

  • Performance Monitoring and Troubleshooting: learn how to screen key performance metrics, discover bottlenecks, and troubleshoot commonplace MongoDB issues for optimal database fitness.

  • Beyond the Basics:  Our comprehensive curriculum may also cover advanced topics like:

  • Aggregation Framework: Learn how to perform complex data transformations and aggregations for insightful data analysis.

  • Geospatial Queries: Explore MongoDB's geospatial capabilities for efficient location-based queries.

  • MongoDB and Cloud Deployment: Understand the considerations for deploying your MongoDB databases in a cloud environment.

Advanced Topics in MongoDB


1. Aggregation Framework:

Go beyond basic queries: The Aggregation Framework is your gateway to executing complex data transformations seamlessly. Dive into the capability to group, filter, sort, and calculate statistics on your data, transcending the limitations of conventional queries. It's a dynamic approach that propels your data manipulation to a whole new level.

Reveal the Unseen: The magic of the Aggregation Framework lies in its ability to unveil hidden patterns and trends lurking within your data. Through skillful utilization of aggregation pipelines, you gain the ability to extract insights that go beyond surface-level observations. This empowering feature equips you to make informed, data-driven decisions with a profound understanding of your information landscape.

Examples: Let the Aggregation Framework be your ally in deciphering meaningful insights. Calculate average order values effortlessly, group products by category for a comprehensive inventory analysis, or identify the most popular items over a specific time period. These are just a glimpse of the possibilities that unfold within the realm of the Aggregation Framework.


2. Geospatial Queries:

Location-based data: For applications that involve geographical data, MongoDB's geospatial capabilities come into play. You can efficiently store and query data based on location coordinates (longitude and latitude).

Unlocking location-aware features: Imagine building a recommendation system for nearby restaurants or a real-time tracking application. Geospatial queries empower you to create location-aware features within your MongoDB applications.

Examples: Find stores within a specific radius of a user's location, track the movement of assets on a map, or create geofences for triggering location-based events.


3. Text Search with MongoDB Atlas Search:

Full-text search capabilities: While MongoDB itself doesn't have built-in text search functionality, MongoDB Atlas Search (a separate offering) provides a powerful solution. It allows you to perform full-text searches across your MongoDB data, including text fields within documents.

Enhanced user experience: Imagine a user searching for products on an e-commerce platform. MongoDB Atlas Search enables efficient searches based on keywords, improving the user experience significantly.

Examples: Search for products by name or description, filter articles based on keywords, or implement auto-completion functionality for search bars.


4. Change Streams and Real-time Applications:

Capturing data changes: Change streams in MongoDB allow you to capture data modifications (inserts, updates, deletes) as they arise in real-time. This opens doors for building reactive applications that respond to data changes instantly.

Building dynamic and responsive systems: Change streams enable applications to react to data updates in real-time. For instance, stock prices can be updated on a live dashboard, or chat messages can be delivered instantly to users.

Examples: Implement role-based access control (RBAC) to restrict user permissions, encrypt sensitive data at relaxation and in transit, and configure audit logs for tracking user activity.


5. Security and Compliance:

Robust security measures: As you deal with sensitive data, ensuring robust security is paramount. MongoDB offers various security features like user authentication, authorization, and encryption to safeguard your data.

Compliance considerations: Depending in your industry and records privacy policies, you would possibly need to adhere to specific compliance standards. MongoDB provides features and tools to help you meet these compliance requirements.

Examples: Implement role-based access control (RBAC) to restrict user permissions, encrypt sensitive data at rest and in transit, and configure audit logs for tracking user activity.


6. Sharding and Distributed Systems:

Scaling for massive datasets: For exceptionally large datasets, sharding allows you to distribute data across multiple servers (shards). This approach enhances performance and scalability as your data volume grows.

Handling horizontal scaling: Sharding enables horizontal scaling, wherein you can upload extra servers to deal with increasing data demands. This ensures your database does not come to be a bottleneck as your application grows.

Examples: Sharding customer data across multiple servers in a large e-commerce platform, distributing social media user data across a sharded cluster, or scaling a gaming application to handle millions of players.



1. Introduction to MongoDB

2. MongoDB Basics

3. Querying and Indexing

4. Aggregation Framework

5. MongoDB and Application Development

6. Security in MongoDB

7. Sharding and Replication

8. Backup and Restoration

9. MongoDB Atlas

10. Real-world Use Cases and Project

Course Content

Introduction to MongoDB and NoSQL Databases

  • Understanding the basics of MongoDB and its role as a NoSQL database.
  • Exploring the advantages of using MongoDB for flexible data modeling and scalability.

Data Modeling with MongoDB

  • Learning how to design and structure data as JSON-like documents.
  • Understanding the concept of schemaless data modeling in MongoDB.

CRUD Operations in MongoDB

  • Mastering CRUD (Create, Read, Update, Delete) operations to manage data in MongoDB collections.
  • Hands-on exercises to perform various data manipulation tasks.

Querying Data in MongoDB

  • Exploring various query methods and operators to retrieve data based on specific criteria.
  • Implementing advanced querying techniques using indexes and aggregation.

Indexes and Performance Optimization

  • Understanding the importance of indexing in MongoDB for faster query performance.
  • Implementing index strategies and analyzing query performance.

Working with Embedded Documents and Arrays

  • Handling nested data structures, such as embedded documents and arrays.
  • Practical examples to manage complex data relationships.

Aggregation Framework

  • Learning how to perform complex data aggregations using MongoDB's powerful aggregation pipeline.
  • Aggregating and grouping data for insightful analysis.

Data Replication and Sharding

  • Exploring data replication for high availability and fault tolerance.
  • Understanding sharding for horizontal scalability and distributed data storage.

Security and Authentication in MongoDB

  • Implementing security measures to protect MongoDB databases.
  • Setting up user authentication and access control.

Backup and Restore Strategies

  • Learning how to perform backups and restores for data protection and disaster recovery.
  • Implementing backup strategies to ensure data integrity.

Real-World Projects and Case Studies

  • Working on practical projects and case studies to apply MongoDB concepts to real-world scenarios.
  • Hands-on experience in building MongoDB-powered applications.

Best Practices and Performance Optimization

  • Understanding best practices for efficient data management in MongoDB.
  • Optimizing MongoDB performance for high-throughput applications.

Mongo DB Training FAQ's

MongoDB is a popular open-source NoSQL database. MongoDB is a document-oriented database management system. It can stores data like JSON structure called documents. Its also called as NoSQL database 

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