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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: Sundog Education by Frank Kane

Last updated July 2025

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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

How it compares

Against the other 150 rated Udemy courses in Hadoop on CourseDuck:

  • Rating4.4 out of 5higher than 54% of them
  • Reviews2,995#25 of 151 by number of reviews
  • Length5.1 hoursshorter than 57% of them
  • Last updatedJuly 2025more recently than 74% of them

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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."

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Instructor Details

Sundog Education by Frank Kane

Sundog Education's mission is to make highly valuable career skills in data engineering, data science, generative AI, AWS, and machine learning accessible to everyone in the world. Our consortium of expert instructors shares our knowledge in these emerging fields with you, at prices anyone can afford. 

As a senior manager at Amazon during its early years, Frank Kane led large technical teams, managed multi-year projects, and served as a "bar-raiser" - interviewing thousands and hiring hundreds across the company.

Frank holds 26 issued patents in machine learning and personalization. After 9 years at Amazon and IMDb, he founded Sundog Education and has since taught over 1.1 million people in AI, ML, AWS, system design, and tech leadership. Frank has been teaching full-time for over 10 years - but is always building projects on the side with the latest emerging technologies, to better explain them to you!

Our teaching style is to simplify complex concepts - once you cut through all the notation and jargon, most of AI and machine learning is pretty easy to understand. We make these advanced topics accessible to anyone with a modest technical background, always using plain English and examples to drive it home. We make learning easy, hands-on, and fun.

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Reviews

4.4

2,995 ratings on Udemy

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By Harsh Prakash on 11/25/2023

Great course as usual from Frank. He is really the genius in this field. His explanation of each topics along with proper examples makes the concept look more easy. Can't Thank enough. Keep doing this great job and makes course on Hive, Pig and other Big data Technologies as a whole complete course. Thanks Again!

By Anonymized User on 11/7/2019

The instructor was awesome! I would prefer to learn more about mapreduce and mrjob than passing very quickly through other technologies

By Roland on 9/12/2018

The hands on approach makes it easy to understand the big data concepts. The programming exercise provides a good head start to someone who is looking to develop an in-depth development skills. Good course!

By Gary Stafford on 3/30/2018

I thought the course was a very good introduction to Hadoop, MRJob, and AWS EMR. The numerous examples were well thought out and a useful learning tool. They were easy to complete and extend. My two suggestions: 1. Some of the videos are getting pretty dated, from 2015. Even if the information is still relevant, knowing the content was recorded 2-3 years ago is a bit disconcerting. 2. I thought the transition from the basic MR examples to the Super Hero example with BFS was a sudden jump in comprehension from the previous, simpler examples. I might suggest placing this a bit later in the course. I would certainly complete a course on Spark from the author.

By Joseph Brown on 3/6/2018

This class would get five stars but it's a little out of date and the instructor is not keeping up with changes in the environment, nor providing much support in the Q&A. Still, if you are willing to do a little extra work figuring out how to get the examples working, this class is well worth the time, providing a rapid introduction to MapReduce.

By Satish Kumar Singh on 3/17/2017

The course is old and hasn't been duly updated. The quality of the video isn't great. And you really need to know Python quite well to get anything real (read the more complex examples, easy ones are too easy anyway) out of it. The way of teaching is not at all engaging. It got so many reviews because it is one of the early courses to be available on Udemy.

By KARTHIKEYAN R on 3/14/2016

Course structure is very good starting from basic WordCount to BreadthFirst Search algorithms using Map reduce....It will be good to include short lecture on how to run MRJOB on our own hadoop cluster instead of EMR. Don't need to explain how to setup cluster, instead live example of running on existing cluster.

By Vijay Venugopalan on 1/23/2016

I really found this course useful and learnt a lot. Just a couple of thoughts: - It would be useful to include a slide or 2 explaining how the MRJob framework works. I had to look that up separately. - This tutorial did not cover anything about Partitioners and how they actually work. It seems like thats a concept thats' well abstracted by the MRjob framework but nevertheless something useful to know about.

By Parekh Utkarsh on 11/26/2015

Really helpful video for study..I learned lot of things. The instructor is awesome..His response to the question is very quickly..I appreciate to him.. I am looking for career in Data Mining and Big Data System and Data Analysis. And this tutorial and instructor are giving me such a good start. Thanks again..

By Senthil on 10/28/2015

This is a great course for someone who wants to explore the complicated world of Big Data and get some understanding on some of the key technologies in this area. Frank Kane does a good job of simplyfing very complex technology and it gives you the confidence to continue to explore and understand Big Data applications.

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Overall Score : 88 / 100