Hadoop Course Introduction

Course overview
9 HOURS OF TRAINING
1 SKILL
21 VIDEOS
1 VIRTUAL LAB
0 PRACTICE EXAMS
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Garth Schulte
Nugget trainer since 2002
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Apache Hadoop FAQs: Cost, Training, Value

What will you learn in this Apache Hadoop training?

This course in Apache Hadoop explains two things especially well. First, it explains the underlying theory of what Apache Hadoop actually does – distributing the processing of large data sets across clusters. Second, it provides opportunities to learn and practice how to actually use Hadoop's many, many different open-source utilities.

Who should take this Apache Hadoop course?

This Apache Hadoop course is best for anyone who works in DevOps, or anyone trying to introduce DevOps tools to their job. The Apache Hadoop utilities are all capable of distributed problem solving and automated improvements. The sorts of solutions Hadoop provides are what DevOps professionals like implementing.

Is this training in Apache Hadoop associated with any certifications?

No, this Apache Hadoop training wasn't designed to correspond with any certifying exams. This course was developed to explain Apache Hadoop's many different utilities and show how to integrate them into a network. The course could prepare you for an exam – but it's best for understanding and using Hadoop.

What certification should you consider after taking this course in Apache Hadoop?

There are a handful of certifications that focus on Apache Hadoop, but unless you know you need a specific one, you may want to broaden your search to a broad DevOps or technology-oriented certification. Certs in Hadoop are private and usually relate to using Hadoop in a narrow context.

Why should you take this Apache Hadoop training?

You should take this Apache Hadoop training so you can use and manage the collection of utilities that makes it possible to distribute big data problem-solving across whole networks. Without training like this, DevOps professionals have to figure out Hadoop's storage, data and cloud-native utilities on their own.

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