MongoDB

Course Duration: 32 Hours of Comprehensive Learning

Mode of Learning:

Choose the learning style that best fits your schedule and preferences:

Online Instructor-Led Training – Learn in real time with live expert-led sessions.
Online Self-Paced Learning – Study anytime, anywhere with flexible recorded modules.
Onsite/Classroom Training – Experience in-person, hands-on learning guided by certified trainers.

What’s Included in the Training Program:

Our industry-leading Training Program is designed to provide a complete learning experience through a perfect blend of theory and practical exposure. Here’s what you’ll get:

Live, Instructor-Led Online Training Sessions
Hands-on Lab Exercises
Certified and Experienced Trainers
Post-Training Support & Mentorship
Comprehensive Learning Resources including eBooks, guides, and reference materials.
Real-World Case Studies & Application Scenarios
Networking Opportunities
Group Projects and Collaborative Learning Activities
Best Practices and Industry Insights.
Access to Recorded Sessions (available for online learners, based on client permissions).
Follow-up Review Sessions.
Tool Demonstrations and Guided Walkthroughs

This training helps you gain the knowledge and hands-on experience needed to advance your career in today’s competitive IT landscape.

Course Content

Introduction to NoSQL and MongoDB

Overview of NoSQL databases and their use cases
What is MongoDB? Why MongoDB?
MongoDB architecture and components (Database, Collections, Documents)
Benefits of MongoDB over traditional RDBMS
Setting up MongoDB (Installation, configuration, and MongoDB Compass)

Course Duration: 32 Hours of Comprehensive Learning

Mode of Learning:

What’s Included in the Training Program:

Course Content

Introduction to NoSQL and MongoDB

Overview of NoSQL databases and their use cases

What is MongoDB? Why MongoDB?

MongoDB architecture and components (Database, Collections, Documents)

Benefits of MongoDB over traditional RDBMS

Setting up MongoDB (Installation, configuration, and MongoDB Compass)

MongoDB Data Model

Collections and Documents in MongoDB

Data types and structure of documents (BSON format)

Schema design considerations (embedding vs. referencing)

Working with MongoDB shell and basic commands

Introduction to MongoDB Compass for GUI-based operations

CRUD Operations in MongoDB

Creating, Reading, Updating, and Deleting documents

The MongoDB query language (find(), insert(), update(), delete())

Using query filters and operators for more complex queries

Updating documents and operators (set, unset, push, pull)

Deleting documents and handling errors

Advanced Querying in MongoDB

Using comparison operators ($gt, $lt, $eq, etc.)

Logical operators (AND, OR, NOR, etc.)

Regular expressions in queries

Projection and sorting results

Indexes in MongoDB: Types (single field, compound, geospatial) and usage

Aggregation Framework

Introduction to aggregation in MongoDB

The aggregation pipeline: stages and operators

Grouping, filtering, and sorting with aggregation

$match, $group, $sort, $project, $lookup, and $unwind

Real-world examples of using aggregation for reporting and analytics

MongoDB Indexing

Importance of indexing for performance

Types of indexes in MongoDB (single field, compound, text, hashed)

Creating and managing indexes

Using explain() to analyze query performance

Index optimization techniques and best practices

MongoDB Performance Tuning

Monitoring MongoDB performance (using tools like mongostat and mongotop)

Analyzing query performance and optimizing queries

Understanding the role of indexes in performance

Profiling and logging slow queries

Caching strategies and connection pooling

Security in MongoDB

MongoDB authentication and authorization

Role-based access control (RBAC)

Encrypting data in MongoDB (Encryption at rest, TLS/SSL for communication)

Auditing and securing MongoDB deployments

Best practices for securing MongoDB instances

Replication in MongoDB

Introduction to replication in MongoDB

Setting up replica sets for data redundancy and high availability

Understanding primary and secondary nodes

Handling automatic failover and election process

Monitoring replication status and health

Sharding in MongoDB

Introduction to sharding and its use cases

Shard key selection and partitioning strategies

Setting up sharding in MongoDB

Managing and monitoring sharded clusters

Balancing data across shards and handling chunk migrations

Backup and Restore in MongoDB

Backup strategies in MongoDB (Mongodump, filesystem snapshots)

Restoring data using mongorestore

Backup best practices and disaster recovery

Automating backup and restore processes

MongoDB Use Cases and Real-World Applications

Real-world use cases: Social media apps, e-commerce platforms, content management systems

Choosing MongoDB for your application: When to use MongoDB over SQL databases

Data modeling for scalable applications

Case studies on large-scale MongoDB deployments

Final Project and Wrap-Up

Hands-on final project: Building a small application using MongoDB

Integrating MongoDB with a simple front-end or backend application (Node.js, Python, etc.)

Code review and troubleshooting

Recap of all concepts and closing thoughts