enthalten
Apache Kafka is an open-source distributed stream processing platform that provides high-throughput and low latency real-time messaging. More than 80% of all Fortune 100 companies trust, and use Kafka. Companies like Airbnb, Netflix, Microsoft, Intuit, Target, etc. use Kafka extensively.
This specialization is designed for individuals seeking to develop proficiency in Apache Kafka, a leading platform for building real-time data pipelines and streaming applications. Kafka is widely adopted by organizations for its scalability, fault tolerance, and high throughput, enabling efficient data integration across various systems.
This is a 4-course series. These courses will cover topics such as Kafka fundamentals, detailed architecture and internals, advanced monitoring and stream processing techniques, integration with other big data tools like Storm, Spark, and Flume, and ensuring robust security practices.
Basics of Java/Scala programming is required for this specialization.
The specialization starts from the basics, making it ideal for beginners to Kafka. It includes hands-on labs, practical demos, quizzes, and high-quality instructional videos from industry experts. This course series provides everything you need to understand Apache Kafka better and effectively implement and manage Kafka-based solutions in real-world scenarios.
Praktisches Lernprojekt
This Apache Kafka specialization offers 19 demos to equip learners with essential skills for building real-time streaming data pipelines and applications using Apache Kafka. Key projects include installing Zookeeper and Kafka, setting up single-node and multi-node clusters, creating Kafka producers and consumers, and working with custom serializers and deserializers. Learners will gain hands-on experience in Kafka installation, cluster configuration, producer and consumer creation, custom serialization, Mirror Maker setup, and Kafka Schema Registry integration. These projects prepare learners to manage Kafka clusters, implement real-time data processing, and ensure secure data streaming, supported by a thorough understanding of Kafka's architecture and capabilities upon completion.
