About this Course

Learn how to tackle big data problems with your own Hadoop clusters! In this course, you’ll deploy Hadoop clusters in the cloud and use them to gain insights from large datasets.

Course Cost
Free
Timeline
Approx. 3 weeks
Skill Level
Intermediate
Included in Course
  • Icon course 01 3edf6b45629a2e8f1b490e1fb1516899e98b3b30db721466e83b1a1c16e237b1 Rich Learning Content

  • Icon course 04 2edd94a12ef9e5f0ebe04f6c9f6ae2c89e5efba5fd0b703c60f65837f8b54430 Interactive Quizzes

  • Icon course 02 2d90171a3a467a7d4613c7c615f15093d7402c66f2cf9a5ab4bcf11a4958aa33 Taught by Industry Pros

  • Icon course 05 237542f88ede3178ac4845d4bebf431ddd36d9c3c35aedfbd92e148c1c7361c6 Self-Paced Learning

  • Icon course 03 142f0532acf4fa030d680f5cb3babed8007e9ac853d0a3bf731fa30a7869db3a Student Support Community

Join the Path to Greatness

This free course is your first step towards a new career with the Business Analyst Nanodegree Program.

Free Course

Deploying a Hadoop Cluster

Enhance your skill set and boost your hirability through innovative, independent learning.

Icon steps 54aa753742d05d598baf005f2bb1b5bb6339a7d544b84089a1eee6acd5a8543d

Course Leads

  • Mat Leonard
    Mat Leonard

    Instructor

What You Will Learn

Lesson 1

Deploying a Hadoop cluster on Amazon EC2

  • Learn how to deploy a small Hadoop cluster on Amazon EC2 instances.
Lesson 1

Deploying a Hadoop cluster on Amazon EC2

  • Learn how to deploy a small Hadoop cluster on Amazon EC2 instances.
Lesson 2

Deploy a Hadoop cluster with Ambari

  • Use Apache Ambari to automatically deploy a larger, more powerful Hadoop cluster.
Lesson 2

Deploy a Hadoop cluster with Ambari

  • Use Apache Ambari to automatically deploy a larger, more powerful Hadoop cluster.
Lesson 3

On-demand Hadoop clusters

  • Use Amazon’s ElasticMapReduce to deploy a Hadoop cluster on-demand.
Lesson 3

On-demand Hadoop clusters

  • Use Amazon’s ElasticMapReduce to deploy a Hadoop cluster on-demand.
Lesson 4

Analyzing a big dataset with Hadoop and MapReduce

  • Use Hadoop and MapReduce to analyze a 150 GB dataset of Wikipedia page views.
Lesson 4

Analyzing a big dataset with Hadoop and MapReduce

  • Use Hadoop and MapReduce to analyze a 150 GB dataset of Wikipedia page views.

Prerequisites and Requirements

This course is intended for students with some experience with Hadoop and MapReduce, Python, and bash commands.

You’ll have to be able to work with HDFS and write MapReduce programs. You can learn about these in our Intro to Hadoop and MapReduce course.

The MapReduce programs in the course are written in Python. It is possible to use Java and other languages, but we suggest using Python, on the level of our Intro to Computer Science course.

You’ll also be using remote cloud machines, so you’ll need to know these bash commands:

  • ssh
  • scp
  • cat
  • head/tail

You’ll also need to be able to work in an editor such as vim or nano. You can learn about these in our Linux Command Line Basics course.

See the Technology Requirements for using Udacity.

Why Take This Course

Using massive datasets to guide decisions is becoming more and more important for modern businesses. Hadoop and MapReduce are fundamental tools for working with big data. By knowing how to deploy your own Hadoop clusters, you’ll be able to start exploring big data on your own.

What do I get?
  • Instructor videos
  • Learn by doing exercises
  • Taught by industry professionals

Thanks for your interest!

We'll be in touch soon.

Icon globe e82eae5d45465aba4fbe4bb746905ce55dc3324f310b79c60e4a20089057d347

Udacity 现已提供中文版本! A Udacity tem uma página em português para você! There's a local version of Udacity for you! Sprechen Sie Deutsch?

Besuchen Sie de.udacity.com und entdecken Sie lokale Angebote, unsere Partnerunternehmen und Udacitys deutschsprachigen Blog.

前往优达学城中文网站 Ir para a página brasileira Go to Indian Site Icon flag de deedb1a7a695700236cb6ef4204ddbede5d197dab9b47716c87a0b4d5d9fc325 Zu de.udacity.com continue in English