Course Outline

🔹 Day 1: Introduction to MongoDB and CRUD Operations

Session 1: MongoDB Overview & Setup

• NoSQL vs. SQL databases
• Key MongoDB concepts: documents, collections, databases
• Installing MongoDB and using MongoDB Compass or Atlas

Session 2: Data Modeling and Schema Design

• Flexible schema approach
• Embedding vs. referencing documents
• Choosing the right data structure

Session 3: CRUD Operations

• Insert, find, update, delete documents
• Query operators and projections
• Working with ObjectId, arrays, and nested fields

Lab Activities:

• Set up a local or cloud MongoDB instance
• Create a database and perform CRUD operations using Mongo Shell or Compass
• Model sample data for a blogging or e-commerce app

🔹 Day 2: Queries, Indexing & Aggregation Pipelines

Session 1: Advanced Query Techniques

• Logical, comparison, and array operators
• Sorting, limiting, skipping results
• Regex and text search

Session 2: Indexing for Performance

• Why indexing matters
• Creating single field, compound, and multikey indexes
• Indexing strategies for optimization

Session 3: Aggregation Framework

• Aggregation pipeline basics
• Stages: $match, $group, $project, $sort, $limit
• Transforming and grouping data effectively

Lab Activities:

• Build complex queries with filters and projections
• Create and compare queries with and without indexes
• Use aggregation pipelines to generate reports and analytics

🔹 Day 3: Application Integration & Performance Tuning

Session 1: Connecting MongoDB with Applications

• Using MongoDB with Node.js (Mongoose or native driver)
• Basic CRUD operations in an app context
• Schema validation and middleware (with Mongoose)

Session 2: Data Integrity & Security

• Schema validation using JSON schema
• Role-based access control and user management
• Backup, restore, and replication basics

Session 3: Performance & Real-World Practices

• Query optimization and explain plans
• Sharding concepts for scalability
• Best practices for working with large collections

Lab Activities:

• Connect a sample app to MongoDB using Mongoose
• Add schema validation and enforce constraints
• Analyze and optimize queries using explain() and index strategies