Confluent Certified Developer for Apache Kafka || 2026 ||

What you'll learn

Understand the fundamentals of event streaming and how Apache Kafka fits into modern data architectures
Learn Kafka core architecture, including brokers, topics, partitions, offsets, and replication
Gain knowledge of Kafka cluster components such as ZooKeeper and KRaft mode
Understand data durability, fault tolerance, and in-sync replicas (ISR)
Build and configure Kafka producers for real-world applications
Apply different message partitioning strategies and key distribution techniques
Master delivery semantics: at-most-once, at-least-once, and exactly-once
Handle retries, failures, and error scenarios in producers
Develop Kafka consumers and work with consumer groups effectively
Understand partition rebalancing and consumer group coordination
Learn offset management and committing strategies
Handle deserialization issues and problematic messages (poison pills)
Design and implement stream processing applications using Kafka Streams
Understand the difference between KStream and KTable and their use cases
Perform stateless and stateful stream operations
Understand streams vs. tables and push vs. pull queries in ksqlDB
Implement authentication, authorization, and role-based access control (RBAC)
Build scalable, fault-tolerant, and real-time data streaming systems
Gain practical skills to work with Kafka in production environments

Requirements

No prior experience with Apache Kafka is required — this course starts from the fundamentals and gradually moves to advanced topics

Description

This course contains the use of artificial intelligence.
This is an Unofficial Course.
This comprehensive course is designed to take you from a complete beginner to a confident, job-ready professional in Apache Kafka and real-time data streaming. In today's data-driven world, organizations rely heavily on event-driven architectures to process massive volumes of data in real time, and Apache Kafka has become the industry standard for building scalable, fault-tolerant streaming platforms. This course provides a deep and practical understanding of Kafka's core architecture, development workflows, and advanced stream processing capabilities, enabling you to build production-grade systems with confidence.
You will begin by developing a strong foundation in event streaming concepts and understanding how Kafka fits into modern distributed systems. You will explore the internal architecture of Kafka clusters, including brokers, topics, partitions, offsets, replication mechanisms, and the role of in-sync replicas in ensuring durability and high availability. The course also introduces essential components of the Confluent ecosystem, including the Schema Registry, helping you manage and evolve data schemas effectively in real-world scenarios.
As you progress, you will gain hands-on experience building Kafka producers and consumers, learning how messages are produced, partitioned, and delivered across distributed systems. You will master critical configuration settings, understand delivery guarantees such as at-most-once, at-least-once, and exactly-once semantics, and learn how to handle retries, failures, and edge cases that commonly occur in production environments. On the consumer side, you will explore consumer groups, partition rebalancing, offset management strategies, and efficient polling and threading models to ensure reliable and scalable data consumption.
The course goes beyond basic messaging by introducing Kafka Streams, a powerful library for building real-time stream processing applications. You will learn how to design and implement stream processing topologies, understand the differences between streams and tables, and apply both stateless and stateful operations. You will also explore advanced concepts such as state stores, time semantics, and windowing strategies, enabling you to process and analyze streaming data with precision and flexibility.
In addition to Kafka Streams, you will dive into ksqlDB, a SQL-based streaming platform that allows you to build stream processing applications using familiar query syntax. You will understand how to work with streams and tables in ksqlDB, differentiate between push and pull queries, and use it to simplify complex streaming use cases without writing extensive code.
Security is a critical aspect of any production system, and this course covers essential Confluent security concepts, including authentication, authorization, and role-based access control. You will learn how to secure your Kafka ecosystem and ensure that data access is properly managed across users and applications.
By the end of this course, you will have a complete understanding of Apache Kafka's architecture and ecosystem, along with the practical skills needed to design, develop, and deploy real-time data streaming solutions.
Whether you are a developer, data engineer, or IT professional, this course equips you with the knowledge and confidence to work with Kafka in real-world environments and advance your career in modern data engineering.
Thank you

Who this course is for

Developers who want to build real-time, event-driven applications using Apache Kafka
Data engineers looking to design and manage scalable data streaming pipelines
Backend engineers interested in distributed systems and high-throughput messaging
Software engineers who want to expand their skills into modern data architectures
Beginners who have basic programming knowledge and want to learn Apache Kafka from scratch
IT professionals and system architects aiming to understand and implement event-driven systems
Professionals preparing for roles in data engineering, streaming platforms, or big data technologies
Anyone interested in learning how modern companies process and analyze data in real time using Apache Kafka and the Confluent ecosystem

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