Learners will build, analyze, and implement real-time data pipelines; produce and consume streaming data; and apply aggregation logic to identify top trending songs using Apache Kafka and Apache Spark. This hands-on course equips learners with practical skills in streaming architecture, data ingestion, transformation logic, and end-to-end pipeline execution.

Throughout the course, learners benefit from a structured, project-based approach that mirrors real industry workflows. They will set up a complete development environment, design a scalable project structure, implement streaming logic in Scala, and write processed data back to Kafka topics. By completing the project, learners gain confidence in working with real-time event data—one of the most in-demand capabilities in today’s data engineering roles. What makes this course unique is its clear focus on a real-world use case: computing top trending songs from continuous data streams. This contextual approach ensures that learners not only understand Kafka and Spark concepts but also apply them in a meaningful, production-style pipeline. Ideal for aspiring data engineers, developers, and technology professionals seeking practical, industry-relevant streaming expertise.