What you'll learn

Skills you'll gain

There are 12 modules in this course

As you progress, you'll delve into advanced Hadoop programming with tools like Pig, Hive, and Spark. These modules are designed to give you hands-on experience with real-world datasets, allowing you to build complex queries, analyze large datasets, and even venture into machine learning with Spark's MLLib. The course also covers integrating relational and non-relational databases with Hadoop, ensuring you can handle a wide range of data scenarios in your career. The final sections focus on managing and optimizing your Hadoop cluster, introducing you to tools like YARN, ZooKeeper, Oozie, and Kafka. You’ll learn how to feed data into your cluster efficiently, manage resources, and analyze streaming data in real time. By the end of this course, you’ll be well-equipped to design and implement Hadoop-based solutions in any data-driven environment. This course is ideal for data engineers, software developers, and IT professionals who have a basic understanding of programming and data management. Familiarity with Java, SQL, and Linux command-line interfaces is recommended but not required.

Using the Hadoop's Core: Hadoop Distributed File System (HDFS) and MapReduce

Programming Hadoop with Pig

Programming Hadoop with Spark

Using Relational Datastores with Hadoop

Using Non-Relational Data Stores with Hadoop

Querying Data Interactively

Managing Your Cluster

Feeding Data to Your Cluster

Analyzing Streams of Data

Designing Real-World Systems

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