Free Course
Deploying a Hadoop Cluster
Analyze Data with Hadoop and MapReduce
Nanodegree Program
Machine Learning Engineer
Become a Machine Learning Engineer
Accelerate your career with the credential that fast-tracks you to job success.
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 Product
Rich Learning Content
Interactive Quizzes
Taught by Industry Pros
Self-Paced Learning
Student Support Community
Join the Path to Greatness
This course is your first step towards a new career with the Machine Learning Engineer Program.
Free Course
Deploying a Hadoop Cluster
Enhance your skill set and boost your hirability through innovative, independent learning.
Course Leads
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 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 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?
Related Free Courses
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Free Course
Deploying a Hadoop Cluster
Analyze Data with Hadoop and MapReduce
Nanodegree Program
Machine Learning Engineer
Become a Machine Learning Engineer
Accelerate your career with the credential that fast-tracks you to job success.
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 Product
Rich Learning Content
Interactive Quizzes
Taught by Industry Pros
Self-Paced Learning
Student Support Community
Join the Path to Greatness
This course is your first step towards a new career with the Machine Learning Engineer Program.
Free Course
Deploying a Hadoop Cluster
Enhance your skill set and boost your hirability through innovative, independent learning.
Course Leads
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 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 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.