Data Processing with Apache Kafka

Data Processing with Apache Kafka focuses on equipping participants with comprehensive skills in handling real-time data streams. The course emphasizes practical applications through a project-based approach, allowing learners to engage directly with the technology and apply their knowledge to real-world scenarios. Participants will explore the architecture of Apache Kafka, its ecosystem, and how to leverage its capabilities for efficient data processing and analysis.
The curriculum is designed to enhance participants' understanding of data flow, message handling, and stream processing. By the end of the course, learners will be able to implement Kafka solutions that meet industry standards. They will also have opportunities to publish their project findings in Cademix Magazine, fostering a culture of knowledge sharing and professional growth within the community.
Introduction to Apache Kafka: Architecture and Components
Setting Up Kafka: Installation and Configuration
Understanding Kafka Topics and Partitions
Producer and Consumer APIs: Implementation and Use Cases
Stream Processing with Kafka Streams
Data Serialization and Deserialization Techniques
Integrating Kafka with Big Data Technologies (Hadoop, Spark)
Monitoring and Managing Kafka Clusters
Error Handling and Data Recovery Strategies
Final Project: Develop a Real-Time Data Processing Application using Kafka

To develop expertise in real-time data processing using Apache Kafka and to apply this knowledge in practical scenarios.

Graduates, job seekers, business professionals, and optionally researchers or consultants.

Basic understanding of programming concepts and familiarity with data analytics tools.