Udemy – Apache Flink | A Real Time & Hands-On course on Flink 2020-10

Udemy – Apache Flink | A Real Time & Hands-On course on Flink 2020-10 Downloadly IRSpace

Apr 17, 2025 - 09:57 Updated: Apr 20, 2025 - 18:06

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Udemy – Apache Flink | A Real Time & Hands-On course on Flink 2020-10

Apache Flink | A Real Time & Hands-On course on Flink published by Udemy Academy. A complete, in-depth, hands-on course on a technology better than Spark for stream processing, namely Apache Flink

Apache Flink is the successor of Hadoop and Spark. It is the next generation Big Data engine for Stream processing. If Hadoop is 2G, Spark is 3G, Apache Flink is 4G in big data stream processing frameworks. Actually, Spark wasn’t a real stream processing framework, it was just a temporary job to do it, but Apache Flink is a real stream engine with extra capacity to do batch, graph, table processing and also run machine learning algorithms. Apache Flink is the latest Big Data technology and is growing rapidly in the market. It is assumed that just as Apache Spark replaced Hadoop, Flink can also replace Spark in the near future. The demand for Flink in the market is increasing. Big companies like Capital One (banking), Alibaba (e-commerce), Uber (transportation) have already started using Apache Flink for their real-time big data processing, and thousands more are diving in.

What you will learn in the Apache Flink | A Real Time & Hands-On course on Flink course:

Learn a cutting edge and latest Apache stream processing framework, Flink.
Learn technology that is much faster than Hadoop and Spark.
Understand the functionality of each Apache Flink component with HANDS-ON Practicals.
Even learn concepts that are not properly explained in Flink’s official documentation.
Solve real-time business case studies using Apache Flink.
The datasets and Flink codes used in the lectures are available in the Resources tab.

Who is this course suitable for:

Students who want to learn Apache Flink from SCRATCH to running a live project.
Those who are new to stream processing and want to learn a stream processing framework that is better than Spark.
Software Engineers who feel like they missed their early entry into Hadoop & Spark.
Hadoop & Spark developers who want to upgrade to Apache’s latest big data streaming engine.