In a data-driven world, real-time processing is no longer optional—it's required. This Apache Kafka Fundamentals is a beginner-friendly but in-depth course for developers, data engineers, system administrators, and IT professionals who want to understand the fundamentals of Apache Kafka and its role in creating modern, high-performance data pipelines.


您将学到什么
Learn Kafka's key features, components, architecture, and industry use cases.
How to Set up Kafka environments and install Zookeeper and Kafka
Learn Kafka producer and consumer basics, configurations, and operations. Work with serializers and deserializers, and manage offsets.
Understand data evolution, the significance of big data, analytics applications, and messaging systems.
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该课程共有3个模块
This module provides an overview of Big Data, messaging systems, and Apache Kafka, including installation and setup demonstrations. By the end of this, learners will be able to install and configure the Kafka environment.
涵盖的内容
16个视频2篇阅读材料4个作业
This module provides an overview of Kafka Producer, covering its architecture and configuration. By completing this module, learners will be able to create and configure Kafka Producers, handle message serialization, and manage partitioning.
涵盖的内容
12个视频4个作业
This module introduces Kafka Consumer fundamentals, including consumer groups, offset management, and deserialization techniques. By completing this module, learners will gain the ability to create Kafka Consumers, effectively manage offsets, and implement custom deserializers for efficient data processing.
涵盖的内容
17个视频1篇阅读材料4个作业
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常见问题
The Apache Kafka training course primarily uses Java for coding examples and exercises, as Kafka itself is written in Java. Some exercises may also involve Scala and command-line scripts.
Yes, a course completion certificate is allocated upon completing all graded assignments and quizzes present in the Kafka Fundamentals course.
Prior Kafka knowledge is not required; however, learners should be familiar with programming fundamentals (Java or Python) and comprehend distributed computing ideas.
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