Apache Flink: Build Real-Time Streaming Data Pipelines

This course contains the use of artificial intelligence.

Master real-time data processing with Apache Flink. Build scalable, fault-tolerant, high-throughput streaming pipelines from scratch using production standards.

Course Curriculum

• Data Engineers looking to master real-time distributed stream processing.

• Software Engineers transitioning into data architecture and pipeline development.

• Backend Developers working with Apache Kafka, CDC, or event-driven systems.

• System Architects designing enterprise real-time analytics platforms.

• Build end-to-end streaming data pipelines using Apache Flink and Java.

• Ingest streaming datasets from Apache Kafka, CDC connectors, and enterprise sources.

• Process stateful event streams using the Flink DataStream API.

• Implement tumbling, sliding, and session event-time processing windows.

• Configure event watermarks to manage delayed or out-of-order data streams.

• Utilize state backends including RocksDB for high-volume enterprise state sizes.

• Deliver processing results into transactional production sinks with zero data loss guarantees.

• Recover processing pipelines seamlessly using distributed checkpoints and savepoints.

• Basic knowledge of Java or Object-Oriented Programming principles.

• Familiarity with basic command-line navigation and development environments.

• Basic understanding of data engineering or database concepts.