Course description

Apache Flink represents the evolution in the realm of Big Data, advancing beyond its predecessors, Hadoop and Spark. It stands as a cutting-edge tool for stream processing in the Big Data sector, akin to an upgrade from 3G (Hadoop) and 4G (Spark) to 5G technology. While Spark offered a provisional solution for stream processing,

Apache Flink emerges as a dedicated streaming engine, also capable of handling batch processing, graph and table operations, and machine learning algorithms.

As a frontrunner in Big Data technology, Apache Flink is quickly gaining traction in the industry. It is anticipated that Flink might follow the path of Apache Spark in superseding Hadoop, potentially becoming the new standard in the near future.

The market's interest in Flink is on the rise, with numerous major companies across various sectors adopting Apache Flink for real-time Big Data processing, and many others are exploring its potential.

The course covers:

A comprehensive guide to Apache Flink, starting from the basics to real-time application.

Detailed, hands-on coding examples for each concept in Apache Flink.

Clarification of concepts not clearly explained in the official Flink documentation.

For those not proficient in Java, the course breaks down Flink Java code in an easily understandable manner.

Access to Flink codes and datasets used in the lectures.

Regular updates to course material in line with the latest version of Flink.

Who this course is for:

Students eager to learn Apache Flink from the ground up to practical project implementation.

Individuals new to stream processing and interested in learning a framework more advanced than Spark.

Software engineers who missed early opportunities with Hadoop & Spark.

Hadoop & Spark developers looking to transition to Apache's latest Big Data Streaming Engine.

What will i learn?

• Learn a cutting edge and Apache's latest Stream processing framework i.e. Flink.
• Understand the working of each and every component of Apache Flink with HANDS-ON Practicals.
• Solve Real-Time Business case studies using Apache Flink.
• Learn a technology which is much faster than Hadoop and Spark.
• Datasets and codes used in lectures are available in resources tab.