Apache Kafka
About this course
Master real-time data engineering with a specialization built for Cloud Architects, Data Engineers, DevOps Specialists, Security Analysts, and Consultants who want industry-ready Kafka skills. Unlike generic courses, this program uses rich analogies, visual walkthroughs, and real-world examples—to make complex distributed-system concepts simple and practical. You will start with the fundamentals of Big Data, then learn Kafka's features, architecture, components, and high-impact industry use cases! As you progress, you will then explore Producer and Consumer internals, including poll loops, offsets, deserializers, and essential configurations. What sets this specialization apart is its deep dive into Kafka internals. You will explore replication types, reliability methods, broker configuration, cluster mirroring, and advanced multi-cluster setups, including hub-spoke, active-active, and stretch clusters. You’ll also learn monitoring, schema registry, Kafka Streams, memory management, K-Tables, data pipelines, and managing Kafka Connect via REST. The journey concludes with Apache Storm, Spark RDD operations, Flume connectors, Admin Client, and Kafka security with ACL-based authorization. With Kafka engineers making $109,490 per year on average in the U.S. and up to $177k+ as top earners, and with use increasing across finance, retail, telecom, and AI-based platforms, this specialization provides you with job-ready end-to-end knowledge.
68/100
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- 20/35
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What you'll learn
- understand the architecture and components of Kafka
- learn about producer and consumer internals
- explore Kafka replication types and reliability methods
- implement Kafka security with ACL-based authorization
- manage data pipelines and Kafka Connect via REST
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