Learn the complete lifecycle of real-time data engineering with Apache Kafka and Spark through hands-on projects that mirror production challenges at companies like Netflix, LinkedIn, and Uber. This comprehensive specialization teaches you to design high-availability streaming architectures, optimize Kafka clusters for millions of events per second, implement exactly-once processing semantics, manage schema evolution without downtime, and build real-time dashboards that power instant business decisions. Starting with Kafka performance tuning and progressing through Spark Structured Streaming, CDC pipelines, and production orchestration, you'll gain the skills to architect, implement, and operate enterprise-grade streaming systems. Each course includes practical labs where you'll configure distributed systems, diagnose performance bottlenecks, handle failures gracefully, and deploy pipelines that transform high-velocity data into immediate business value.
Applied Learning Project
Throughout this specialization, you'll complete hands-on projects that simulate real-world streaming challenges: configure Kafka clusters for high availability, implement exactly-once processing pipelines, build CDC systems with schema evolution, create real-time fraud detection engines, develop live operational dashboards, and design multi-region recovery strategies. Each project progresses from foundational setup through production deployment, using Docker environments and cloud-ready architectures that you can immediately apply in professional settings.
