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Sarah Sproehnle,
Ian Wrigley,
and
Gundega Dekena
Take Udacity's free course and get an introduction to Apache Hadoop and MapReduce and start making sense of Big Data in the real world! Learn online with Udacity.
Register for this course and see more details by visiting:
OpenCourser.com/course/5vb8zb/udacity
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What's inside
Syllabus
Big Data
Problem Set
HDFS and MapReduce
MapReduce Code
Read more
Syllabus
Big Data
Problem Set
HDFS and MapReduce
MapReduce Code
Read more
MapReduce Design Patterns
Project [Optional]
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops Big Data, Hadoop, and MapReduce skills, which are core foundational and analytical skills for data scientists and software engineers
Provides an introduction to Big Data and MapReduce, making it accessible to learners new to these concepts
Save this course
Save Intro to Hadoop and MapReduce to your list so you can find it easily later:
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Reviews summary
Hadoop: powerful data processing
Learn how to "make sense of your Big Data" with Hadoop and MapReduce from beginner-friendly to intermediate-level video lessons, exercises, and real-world examples.
Course is accessible to beginners.
"Lesson 1 does not have technical prerequisites and is a good overview of Hadoop and MapReduce for managers."
Course prepares you to work with Big Data.
"Learn the fundamental principles behind it, and how you can use its power to make sense of your Big Data."
Course offers real-world examples.
"I appreciate that it brings real-world examples and lets you try the code on live system, not only udacity coding platform."
Video lessons are short.
"Ridiculously tiny videos, no detailed explanations, disappointed."
Course overviews fundamental principles.
"This is a solid introduction ..."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Intro to Hadoop and MapReduce with these
activities:
Read 'Hadoop: The Definitive Guide'
Show steps
Gain a comprehensive understanding of Hadoop by reading this authoritative book
View
Hadoop: The Definitive Guide: Storage and...
on Amazon
Show steps
-
Read through the chapters on Hadoop architecture, MapReduce, and HDFS.
-
Study the code examples and try implementing them.
-
Refer to the book for reference and further clarification throughout the course.
Review Hadoop And MapReduce
Show steps
Review fundamental Hadoop and MapReduce concepts to build a solid foundation for this course
Browse courses on
Apache Hadoop
Show steps
-
Revisit core Hadoop concepts such as HDFS and YARN.
-
Brush up on MapReduce programming model.
-
Explore Hadoop and MapReduce use cases in real-world scenarios.
Attend Hadoop User Group Meetups
Show steps
Engage with the Hadoop community and learn from experts at user group meetups
Browse courses on
Networking
Show steps
-
Identify local Hadoop User Group meetups in your area or online.
-
Attend meetups to listen to presentations, participate in discussions, and connect with professionals.
-
Share your own experiences and knowledge with the group.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a Hadoop Study Group
Show steps
Collaborate with peers to discuss concepts, share knowledge, and reinforce your learning
Browse courses on
Hadoop
Show steps
-
Join or form a study group with other learners in the course.
-
Meet regularly to discuss course material, solve problems, and share resources.
-
Present your understanding of topics to the group.
MapReduce Code Exercises
Show steps
Engage in hands-on exercises to improve your understanding and coding skills in MapReduce
Browse courses on
MapReduce
Show steps
-
Solve coding problems related to MapReduce concepts.
-
Practice writing MapReduce code snippets.
-
Implement MapReduce solutions for sample datasets.
Explore Hadoop Ecosystem Tools
Show steps
Expand your knowledge of the Hadoop ecosystem by exploring related tools to complement your understanding
Show steps
-
Research and identify tools within the Hadoop ecosystem, such as Hive, Pig, and Sqoop.
-
Follow online tutorials or documentation to learn the basics of each tool.
-
Experiment with the tools on sample datasets to gain practical experience.
Design a MapReduce Solution
Show steps
Design a MapReduce solution from scratch to demonstrate your understanding and problem-solving abilities
Browse courses on
MapReduce
Show steps
-
Identify a data processing problem that can be solved using MapReduce.
-
Design the MapReduce job architecture, including mappers, reducers, and data flow.
-
Implement the MapReduce job with appropriate code.
-
Evaluate the performance and discuss potential optimizations.
Contribute to Hadoop Open Source Projects
Show steps
Make meaningful contributions to the Hadoop community by getting involved in open source projects
Browse courses on
Hadoop
Show steps
-
Identify open source Hadoop projects that align with your interests.
-
Contribute code, documentation, or bug fixes to the projects.
-
Engage with the community by participating in forums and discussions.
Read 'Hadoop: The Definitive Guide'
Show steps
Gain a comprehensive understanding of Hadoop by reading this authoritative book
View
Hadoop: The Definitive Guide: Storage and...
on Amazon
Show steps
Show steps
Show steps
- Read through the chapters on Hadoop architecture, MapReduce, and HDFS.
- Study the code examples and try implementing them.
- Refer to the book for reference and further clarification throughout the course.
Review Hadoop And MapReduce
Show steps
Review fundamental Hadoop and MapReduce concepts to build a solid foundation for this course
Browse courses on
Apache Hadoop
Show steps
Show steps
Show steps
- Revisit core Hadoop concepts such as HDFS and YARN.
- Brush up on MapReduce programming model.
- Explore Hadoop and MapReduce use cases in real-world scenarios.
Attend Hadoop User Group Meetups
Show steps
Engage with the Hadoop community and learn from experts at user group meetups
Browse courses on
Networking
Show steps
Show steps
Show steps
- Identify local Hadoop User Group meetups in your area or online.
- Attend meetups to listen to presentations, participate in discussions, and connect with professionals.
- Share your own experiences and knowledge with the group.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a Hadoop Study Group
Show steps
Collaborate with peers to discuss concepts, share knowledge, and reinforce your learning
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Join or form a study group with other learners in the course.
- Meet regularly to discuss course material, solve problems, and share resources.
- Present your understanding of topics to the group.
MapReduce Code Exercises
Show steps
Engage in hands-on exercises to improve your understanding and coding skills in MapReduce
Browse courses on
MapReduce
Show steps
Show steps
Show steps
- Solve coding problems related to MapReduce concepts.
- Practice writing MapReduce code snippets.
- Implement MapReduce solutions for sample datasets.
Explore Hadoop Ecosystem Tools
Show steps
Expand your knowledge of the Hadoop ecosystem by exploring related tools to complement your understanding
Show steps
Show steps
Show steps
- Research and identify tools within the Hadoop ecosystem, such as Hive, Pig, and Sqoop.
- Follow online tutorials or documentation to learn the basics of each tool.
- Experiment with the tools on sample datasets to gain practical experience.
Design a MapReduce Solution
Show steps
Design a MapReduce solution from scratch to demonstrate your understanding and problem-solving abilities
Browse courses on
MapReduce
Show steps
Show steps
Show steps
- Identify a data processing problem that can be solved using MapReduce.
- Design the MapReduce job architecture, including mappers, reducers, and data flow.
- Implement the MapReduce job with appropriate code.
- Evaluate the performance and discuss potential optimizations.
Contribute to Hadoop Open Source Projects
Show steps
Make meaningful contributions to the Hadoop community by getting involved in open source projects
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Identify open source Hadoop projects that align with your interests.
- Contribute code, documentation, or bug fixes to the projects.
- Engage with the community by participating in forums and discussions.
Career center
Learners who complete Intro to Hadoop and MapReduce will develop knowledge and skills
that may be useful to these careers:
Big Data Architect
Big Data Architect
A Big Data Architect is responsible for designing and building Big Data solutions. This course provides an introduction to Apache Hadoop and MapReduce, which are essential technologies for working with Big Data. By completing this course, Big Data Architects can gain a better understanding of how to design and build Big Data solutions.
Data Scientist
Data Scientist
A Data Scientist is responsible for using data to solve business problems. This course may be useful for Data Scientists as it provides an introduction to Apache Hadoop and MapReduce, which are essential technologies for working with Big Data. Hadoop and MapReduce can help Data Scientists to manage and process large amounts of data efficiently. By completing this course, Data Scientists can gain a better understanding of how to use data to solve business problems.
Business Analyst
Business Analyst
A Business Analyst is responsible for analyzing and solving business problems. This course may be useful for Business Analysts who are interested in working with Big Data. Hadoop and MapReduce are essential technologies for working with Big Data, and this course provides an introduction to these technologies. By completing this course, Business Analysts can gain a better understanding of how to use data to solve business problems.
Statistician
Statistician
A Statistician is responsible for collecting, analyzing, and interpreting data. This course may be useful for Statisticians who are interested in working with Big Data. Hadoop and MapReduce are essential technologies for working with Big Data, and this course provides an introduction to these technologies. By completing this course, Statisticians can gain a better understanding of how to collect, analyze, and interpret Big Data.
Data Warehouse Architect
Data Warehouse Architect
A Data Warehouse Architect is responsible for designing and building data warehouses. This course may be useful for Data Warehouse Architects who are interested in working with Big Data. Hadoop and MapReduce are essential technologies for working with Big Data, and this course provides an introduction to these technologies. By completing this course, Data Warehouse Architects can gain a better understanding of how to design and build data warehouses that can handle large amounts of data.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is responsible for designing and building machine learning models. This course may be useful for Machine Learning Engineers who are interested in working with Big Data. Hadoop and MapReduce are essential technologies for working with Big Data, and this course provides an introduction to these technologies. By completing this course, Machine Learning Engineers can gain a better understanding of how to design and build machine learning models that can handle large amounts of data.
Data Analyst
Data Analyst
A Data Analyst is responsible for collecting, analyzing, and interpreting data. This course may be useful for Data Analysts who are interested in working with Big Data. Hadoop and MapReduce are essential technologies for working with Big Data, and this course provides an introduction to these technologies. By completing this course, Data Analysts can gain a better understanding of how to collect, analyze, and interpret data.
Data Engineer
Data Engineer
A Data Engineer is responsible for building and maintaining data pipelines. This course may be useful for Data Engineers as it provides an introduction to Apache Hadoop and MapReduce, which are essential technologies for working with Big Data. Hadoop and MapReduce can help Data Engineers to process and transform large amounts of data efficiently. By completing this course, Data Engineers can gain a better understanding of how to design and implement data pipelines that can meet the needs of their organization.
IT Manager
IT Manager
An IT Manager is responsible for planning, implementing, and managing an organization's IT infrastructure. This course may be useful for IT Managers who are interested in working with Big Data. Hadoop and MapReduce are essential technologies for working with Big Data, and this course provides an introduction to these technologies. By completing this course, IT Managers can gain a better understanding of how to plan and implement IT infrastructures that can support the needs of their organization.
Systems Analyst
Systems Analyst
A Systems Analyst is responsible for analyzing and designing computer systems. This course may be useful for Systems Analysts who are interested in working with Big Data. Hadoop and MapReduce are essential technologies for working with Big Data, and this course provides an introduction to these technologies. By completing this course, Systems Analysts can gain a better understanding of how to design and analyze computer systems that can manage and process large amounts of data.
Software Engineer
Software Engineer
A Software Engineer is responsible for designing, building, and maintaining software applications. This course may be useful for Software Engineers who are interested in working with Big Data. Hadoop and MapReduce are essential technologies for working with Big Data, and this course provides an introduction to these technologies. By completing this course, Software Engineers can gain a better understanding of how to design and build software applications that can manage and process large amounts of data.
Data Architect
Data Architect
A Data Architect is responsible for designing, building, and maintaining an organization's data architecture. This course may be useful for Data Architects as it provides an introduction to Apache Hadoop and MapReduce, which are essential technologies for working with Big Data. Hadoop and MapReduce can help Data Architects to manage and process large amounts of data efficiently. By completing this course, Data Architects can gain a better understanding of how to design and implement data architectures that can support the needs of their organization.
Database Administrator
Database Administrator
A Database Administrator is responsible for managing and maintaining databases. This course may be useful for Database Administrators who are interested in working with Big Data. Hadoop and MapReduce are essential technologies for working with Big Data, and this course provides an introduction to these technologies. By completing this course, Database Administrators can gain a better understanding of how to manage and maintain databases that can handle large amounts of data.
Project Manager
Project Manager
A Project Manager is responsible for planning, executing, and controlling projects. This course may be useful for Project Managers who are interested in working with Big Data. Hadoop and MapReduce are essential technologies for working with Big Data, and this course provides an introduction to these technologies. By completing this course, Project Managers can gain a better understanding of how to plan and execute projects that involve Big Data.
For more career information including salaries, visit:
OpenCourser.com/course/5vb8zb/udacity
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Intro to Hadoop and MapReduce.
Provides a comprehensive overview of Hadoop and MapReduce. It valuable reference for anyone who wants to learn more about Hadoop and how to use it effectively.
Provides a collection of design patterns for writing MapReduce programs. It useful reference for anyone who wants to learn how to write efficient and effective MapReduce programs.
Save
Provides a practical guide to using Hadoop in the real world. It valuable reference for anyone who wants to learn how to use Hadoop to solve real-world problems.
Save
Provides a gentle introduction to Hadoop. It good starting point for anyone who is new to Hadoop.
Save
Provides a practical guide to using Hadoop. It valuable reference for anyone who wants to learn how to use Hadoop to solve real-world problems.
Provides a gentle introduction to Hadoop. It good starting point for anyone who is new to Hadoop.
Save
Provides a comprehensive overview of Hadoop in the cloud. It valuable reference for anyone who wants to learn more about Hadoop and how to use it in the cloud.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/5vb8zb/udacity
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Via
Udacity
Instructors
Sarah Sproehnle
Ian Wrigley
Gundega Dekena
Language
English
Good to know
Develops Big Data, Hadoop, and MapReduce skills, which are core foundational and analytical skills for data scientists and software engineers
Provides an introduction to Big Data and MapReduce, making it accessible to learners new to these concepts
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