NoSQL Databases (MongoDB, Cassandra, Redis) is a specialized course designed to equip learners with the skills and knowledge necessary to work with modern non-relational database systems that power scalable, high-performance applications across diverse industries. The course begins with a foundational overview of the NoSQL paradigm, contrasting it with traditional relational database management systems (RDBMS). Students are introduced to the CAP theorem, which highlights the trade-offs between consistency, availability, and partition tolerance, helping them understand why NoSQL systems are designed the way they are. Learners explore the four primary categories of NoSQL databases: document stores, key-value stores, column-family stores, and graph databases, with an in-depth focus on MongoDB, Cassandra, and Redis—each representing a major type. In the MongoDB module, learners explore document-based storage using BSON format, performing CRUD operations, advanced querying, indexing strategies, and aggregations using the aggregation pipeline framework. Schema design best practices are taught, including embedding vs. referencing documents, supporting scalable application needs. The course covers replica sets for high availability, sharding for horizontal scalability, and MongoDB Atlas for cloud deployment. In Cassandra, a wide-column store built for massive write throughput and decentralized architecture, learners use CQL (Cassandra Query Language) to create tables, design partition keys and clustering columns, and model time-series data. The course explains Cassandra’s eventual consistency model, tunable consistency levels, replication strategies, and multi-datacenter support. Students set up Cassandra clusters, simulate node failures, and monitor performance with tools like nodetool and OpsCenter. In Redis, an in-memory key-value store optimized for ultra-low latency operations, learners work with fundamental data structures such as strings, lists, sets, sorted sets, and hashes. They explore use cases like caching, pub/sub messaging, distributed locks, and real-time analytics dashboards. Persistence options such as RDB snapshots and AOF (Append Only File) logging are compared, and Redis clustering and sentinel mechanisms are used for high availability and failover. The course includes real-world use cases like building leaderboard systems, user session stores, IoT data ingestion layers, and shopping cart microservices. Integration techniques for connecting NoSQL databases with applications in Node.js, Python, and Java are demonstrated, along with REST APIs and message queues. Security considerations such as authentication, access control, data encryption, and secure configuration practices are addressed. Learners also explore data migration, backup strategies, and monitoring with tools like Prometheus, Grafana, and cloud-native dashboards. By the end of the course, students will have the ability to choose the appropriate NoSQL database for different workloads, design optimal data models, implement distributed, scalable architectures, and troubleshoot performance bottlenecks. Whether aiming to work in real-time systems, social platforms, financial applications, or gaming engines, graduates of this course will be well-prepared to build resilient, high-throughput systems using the strengths of MongoDB, Cassandra, and Redis. This course is ideal for data engineers, backend developers, DevOps professionals, and architects who need to design, deploy, and scale non-relational data solutions in modern application environments.