Taming Big Data with MapReduce and Hadoop Hands On (Udemy.com)

Learn MapReduce fast by building over 10 real examples, using Python, MRJob, and Amazon's Elastic MapReduce Service.

Created by: Frank Kane

Produced in 2021

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What you will learn

  • Understand how MapReduce can be used to analyze big data sets
  • Write your own MapReduce jobs using Python and MRJob
  • Run MapReduce jobs on Hadoop clusters using Amazon Elastic MapReduce
  • Chain MapReduce jobs together to analyze more complex problems
  • Analyze social network data using MapReduce
  • Analyze movie ratings data using MapReduce and produce movie recommendations with it.
  • Understand other Hadoop-based technologies, including Hive, Pig, and Spark
  • Understand what Hadoop is for, and how it works

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Quality Score

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Overall Score : 90 / 100

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Course Description

Big data" analysis is a hot and highly valuable skill and this course will teach you two technologies fundamental to big data quickly: MapReduce and Hadoop. Ever wonder how Google manages to analyze the entire Internet on a continual basis? You'll learn those same techniques, using your own Windows system right at home.

Learn and master the art of framing data analysis problems as MapReduce problems through over 10 hands-on examples, and then scale them up to run on cloud computing services in this course. You'll be learning from an ex-engineer and senior manager from Amazon and IMDb.

Learn the concepts of MapReduce
Run MapReduce jobs quickly using Python and MRJob
Translate complex analysis problems into multi-stage MapReduce jobs
Scale up to larger data sets using Amazon's Elastic MapReduce service
Understand how Hadoop distributes MapReduce across computing clusters
Learn about other Hadoop technologies, like Hive, Pig, and Spark
By the end of this course, you'll be running code that analyzes gigabytes worth of information in the cloud in a matter of minutes.

We'll have some fun along the way. You'll get warmed up with some simple examples of using MapReduce to analyze movie ratings data and text in a book. Once you've got the basics under your belt, we'll move to some more complex and interesting tasks. We'll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We'll analyze a social graph of superheroes, and learn who the most popular" superhero is and develop a system to find degrees of separation" between superheroes. Are all Marvel superheroes within a few degrees of being connected to The Incredible Hulk? You'll find the answer.

This course is very hands-on; you'll spend most of your time following along with the instructor as we write, analyze, and run real code together both on your own system, and in the cloud using Amazon's Elastic MapReduce service. Over 5 hours of video content is included, with over 10 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Hadoop-based technologies, including Hive, Pig, and the very hot Spark framework complete with a working example in Spark.

Don't take my word for it - check out some of our unsolicited reviews from real students:

"I have gone through many courses on map reduce; this is undoubtedly the best, way at the top."

"This is one of the best courses I have ever seen since 4 years passed I am using Udemy for courses."

"The best hands on course on MapReduce and Python. I really like the run it yourself approach in this course. Everything is well organized, and the lecturer is top notch."

Who this course is for:
This course is best for students with some prior programming or scripting ability. We will treat you as a beginner when it comes to MapReduce and getting everything set up for writing MapReduce jobs with Python, MRJob, and Amazon's Elastic MapReduce service - but we won't spend a lot of time teaching you how to write code. The focus is on framing data analysis problems as MapReduce problems and running them either locally or on a Hadoop cluster. If you don't know Python, you'll need to be able to pick it up based on the examples we give. If you're new to programming, you'll want to learn a programming or scripting language before taking this course.

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Instructor Details

Frank Kane

Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.

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Reviews

4.5

312 total reviews

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By Marc Bannout on 10/17/2020

That's fine if you want to learn how mapReduce works but the course is old so there are some things that are obsolete

By Bruno Guimares on 9/4/2020

Excelente curso! O nico problema que foi gravado em 2015 algumas coisas mudaram na biblioteca MRJob (mesmo na verso que eles pedem pra instalar) e no servio EMR da AWS. Porm, um pouco de pesquisa resolve os problemas.

Very nice to start with. Gives good insight into MapReduce, EMR, Hadoop, Spark etc.
Content is 5 yrs old at the time of writing. So needs a refresh of the commands and instructions.

By Vladimir Kuznetsov on 6/11/2020

This course would be better if it had some exercises that require to be solved and verified on your side for graduation. You really learn the material when your solving problems.

By Sbastien Buchoux on 5/11/2020

The course is indeed a great hands-on experience. It is obvious that Frank knows what he speaks about.
The only issue is that the provided code is outdated as mrjob's API has changed so it is needed to update all scripts to be able to run them smoothly.
I took this issue as a part of an exercise but it may be harder for people who are not that familiar with Python.

By Ashwin Narayanan on 5/4/2020

Interesting course to kick start my learning journey on Udemy. The instructor was crisp and precise in his explanation on various real time examples. It helped me understand map reduce functions in detail. Recommend this course if someone is interested to learn Mapreduce

By Radhakrishnan Iyer on 4/8/2020

Cover examples really well.
Makes sure that the student takes in mulitple examples.
all the slides and every other material provided is to the mark.

By Sixing Huang on 11/7/2020

Very good course. Learn a lot in MR

By Philip Solovyev on 4/24/2020

This course is excellent!
It is the clearest explanation for the map reduce concept that I have ever heard. Sometimes code in the video is a little bit outdated because mrjob is continuously evolving, but the changes you need to do to make it work are always in the comments. The responsiveness of Emad, who answers the questions, is worth mentioning too.
I really liked the tasks involving running the scripts on AWS EMR, though I would prefer more activities in general.
Personally Ill continue studying with Frank and the Sundog Education.

By Ming Jun Sim on 7/12/2020

Yes it was a good match. Some technical difficulties while running Spyder in Anaconda, but otherwise it was great!

By Dustin Becker on 4/27/2020

Perfect explanations for people who are familiar with IT and programming, but new into Big Data.

By Vijay Prakash on 8/14/2020

Awesome explanations and good examples for people starting from the basics.