Free Course
Intro to Hadoop and MapReduce
by
How to Process Big Data
Nanodegree Program
Introduction to Programming
Learn to Code
Advance your career by learning the basics of programming.
About this Course
The Apache™ Hadoop® project develops open-source software for reliable, scalable, distributed computing. Learn the fundamental principles behind it, and how you can use its power to make sense of your Big Data.
Course Cost
Free
Timeline
Approx. 1 months
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 Introduction to Programming Program.
Free Course
Intro to Hadoop and MapReduce
Enhance your skill set and boost your hirability through innovative, independent learning.
Course Leads
Sarah Sproehnle
Instructor
Ian Wrigley
Instructor
Gundega Dekena
Instructor
What You Will Learn
lesson 1
Big Data
- What is Big Data?
- The problems big data creates.
- How Apache Hadoop addresses these problems.
lesson 2
HDFS and MapReduce
- Discover how HDFS distributes data over multiple computers.
- Learn how MapReduce enables analyzing datasets in parallel across multiple machines.
lesson 3
MapReduce code
- Write your own MapReduce code.
lesson 4
MapReduce Design Patterns
- Use common patterns for MapReduce programs to analyze Udacity forum data.
Prerequisites and Requirements
Lesson 1 does not have technical prerequisites and is a good overview of Hadoop and MapReduce for managers.
To get the most out of the class, however, you need basic programming skills in Python on a level provided by introductory courses like our Introduction to Computer Science course.
To learn more about Hadoop, you can also check out the book Hadoop: The Definitive Guide.
See the Technology Requirements for using Udacity.
Why Take This Course
- How Hadoop fits into the world (recognize the problems it solves)
- Understand the concepts of HDFS and MapReduce (find out how it solves the problems)
- Write MapReduce programs (see how we solve the problems)
- Practice solving problems on your own