MongoDB Course
Duration: 12 Sessions
Level: Beginner to Advanced
Technology: MongoDB, MongoDB Atlas, NoSQL, BSON, Aggregation Framework, Python, Node.js, Java
Level: Beginner to Advanced
Technology: MongoDB, MongoDB Atlas, NoSQL, BSON, Aggregation Framework, Python, Node.js, Java
Session 1: Introduction to MongoDB and NoSQL Databases
- Overview of MongoDB and NoSQL databases
- Comparison with traditional SQL databases
- Features and advantages of MongoDB
- Setting up MongoDB environment
Practical: Install MongoDB and configure the development environment.
Session 2: MongoDB Data Model
- Document-oriented data model
- BSON (Binary JSON) format
- Collections and Documents
- Schema design best practices
Practical: Create databases, collections and sample MongoDB documents.
Session 3: CRUD Operations in MongoDB
- Inserting documents
- Querying documents
- Updating documents
- Deleting documents
Practical: Perform complete CRUD operations using MongoDB commands.
Session 4: Indexing and Aggregation Framework
- Importance of indexing
- Creating and managing indexes
- Introduction to the Aggregation Framework
- Aggregation pipeline stages
Practical: Create indexes and build basic aggregation pipelines.
Session 5: Data Modeling and Schema Design
- Embedded vs. Referenced Data Models
- One-to-One relationships
- One-to-Many relationships
- Many-to-Many relationships
- Design considerations for various use cases
Practical: Design a MongoDB schema for a real-world application.
Session 6: MongoDB Atlas and Cloud Deployment
- Overview of MongoDB Atlas
- Setting up a MongoDB cluster on the cloud
- Database configuration and management
- Best practices for deploying MongoDB in the cloud
Practical: Create and configure a MongoDB Atlas cluster.
Session 7: Security in MongoDB
- Authentication and Authorization
- Role-Based Access Control
- User and privilege management
- Encryption and SSL/TLS
Practical: Configure users, roles and database access permissions.
Session 8: MongoDB Performance Optimization
- Query optimization techniques
- Indexing strategies
- Profiling and monitoring tools
- Sharding for horizontal scaling
Practical: Analyze queries and optimize database performance.
Session 9: MongoDB and Programming Languages
- MongoDB drivers for different programming languages
- Connecting MongoDB with Python
- Connecting MongoDB with Node.js
- Connecting MongoDB with Java
- Code examples and best practices
Practical: Connect MongoDB with an application using Python, Node.js or Java.
Session 10: Real-World Applications and Case Studies
- Use cases and applications of MongoDB
- Case studies of MongoDB implementations
- Database architecture examples
- Lessons learned and best practices
Practical: Analyze a real-world MongoDB application architecture.
Session 11: Advanced Topics
- Change Streams and Real-Time Data
- Full-Text Search in MongoDB
- Geospatial Queries and Indexes
Practical: Implement advanced MongoDB features using sample datasets.
Session 12: Final Project and Capstone
- Applying knowledge to a real-world project
- Designing and implementing a MongoDB-based application
- Database design and implementation
- Project presentations and feedback
Final Project: Develop and present a MongoDB-based application.
Additional Resources and References
- Recommended readings and documentation
- Online forums and communities
- Further learning paths and certifications
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