Course Review: Taming Big Data with MapReduce and Hadoop

Today we shall be talking in detail about an online course titled “Taming Big Data with MapReduce and Hadoop”. We believe proficiency in “Big Data” analysis clearly stands out in the realm of valuable skills. This course is designed to help you familiarize yourself with two pivotal technologies. One is MapReduce and the other one is Hadoop. Did you ever think about how colossal amounts of data, like the entirety of the internet are managed continuously and efficiently say by Google? 

Taming Big Data with MapReduce and Hadoop
Sundog Education
TTC Rating4.3
Total Reviews Analyzed587
Duration5 Hours
Enrollments24,000+
Skill LevelIntroductory
Course TypeSelf-paced
Accreditation–
Disclaimer! Our comparison is based on authentic learner feedback and aims to provide valuable insights to the learning community. We maintain fairness, objectivity, and accuracy in our assessments.

86%

Sundog Education

Taming Big Data with MapReduce and Hadoop

Total Reviews: 587 Positive Reviews: 503 Neutral Reviews: 58 Negative Reviews: 26

With the help of this course, you will understand all those techniques allowing you to employ them on your own Windows system. This course is an opportunity to grasp the art of framing data analysis problems as MapReduce challenges. The course features over 10 practical examples for an enhanced learning experience. With that, you will learn to scale all these solutions or operate seamlessly on cloud computing services making the course a comprehensive journey into the world of big data.

What you’ll Learn:

  • You will learn how MapReduce is used for analyzing big data sets
  • Then you will be taught how to write your own MapReduce jobs using Python and MRjob
  • Next, you will understand how to run MapReduce jobs on Hadoop clusters using Amazon Elastic MapReduce
  • Similarly, you will learn to chain MapReduce jobs together to analyze complex problems
  • After that, you will be taught how to analyze social network data using MapReduce
  • Going further, the instructor will explain in detail how to analyze movie ratings data using MapReduce and produce movie recommendations with it
  • Then you will understand many Hadoop-based technologies including Hive, Pig, and Spark
  • In addition, you will learn all about Hadoop and how it works

Key Insights (Based on Real Learner’s Feedback)

Key Strength:

Clear and comprehensive instruction

The course was given much appreciation for its instructor’s adeptness in simplifying intricate MapReduce and Hadoop concepts. Learners claimed that the course offers detailed yet understandable explanations that demystified complex topics efficiently.

Interactive hands-on learning

All the practical exercises were highly valued by the students and they appreciated the applicability to real-world scenarios. The following approach led to a deeper understanding of the material, despite a few concerns about the pace and depth of code explanation.

Expertise and engaging teaching style

Frank Kane’s expertise along with his engaging teaching style resonates positively and keeps the learners interested. However, there were some concerns about fast pacing, and also learners felt the need for more detailed code explanations impacting the learning experience.

Structured learning materials

The structure and material of the course were appreciated for their organization and user-friendly nature. Whereas the majority of the praise was given to the well-organized lectures. Some learners also raised their concerns about repetitive examples.

Relevance to practical application

A lot of students appreciated the course’s real-world applicability which emphasized how the content enriched their understanding and ability to apply MapReduce in professional settings.

Accessibility and instructor support

The course’s accessibility and instructor responsiveness were also applauded by the students. The course was especially feasible for beginners. Nonetheless, there were some learners who highlighted challenges with certain concepts and sought more comprehensive explanations.

Preparation for real-world use

This course was deemed as a solid ground for implementing MapReduce practically by learners instilling confidence in their abilities.

Key Challenges:

Outdated material

There were a lot of complaints by users regarding the course featuring outdated content including Python 2.7 usage. Some material was dated back to 2015 leaving the course feeling irrelevant to current industry standards.

Technical challenges with tools

There were multiple reviews expressing frustration over technical obstacles. Some claimed there were a lot of issues during setup and with tools like Enthought Canopy and MRJob that hindered the learning experience.

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Real Learner’s Reviews:

Positive Reviews:

  • The course was no doubt excellent as it offered the clearest explanation for the MapReduce concept that I have ever seen and heard. Yes, sometimes the code in the video was a little bit outdated but that is because MRJob is evolving continuously. But all the changes that you need to do to make it work are always available in the comment section. The responses given by Emad are worth mentioning too. Also, I liked the tasks involving running the scripts on AWS EMR.
  • Overall this is a fantastic course and in no time I was able to run MapReduce jobs on Amazon EMR which otherwise would have taken forever to figure out. I can say if you don’t know Python then I would recommend you learn Python before enrolling in this course as it will be good for you. Also if you are not using Canopy or Python 2 then you may hit some trouble. But don’t worry the instructor will clear all these things in the beginning.
  • The instructor is great and he knows everything and communicates his knowledge excellently. I have a good background in software engineering and am in the middle of looking for a new job. But I don’t know why I am always being called for big data and analytical roles. Now thanks to this course I was able to understand all this.
  • This is a perfect course for all those who wish to learn map-reduce programming. The instructor is great and his explanations for converting real-world problems into MapReduce problems were great.
  • An excellent course that explains in detail how to break a solution into small meaningful chunks in presentation right at the beginning followed by code. The instructor is without any doubt a role model.

Negative Reviews:

  • The instructor of this course is good but the tools for MRJob were broken. With that, I had to use full paths for the rating Counter.py call in Canopy since my user directory was not in my path.
  • I was expecting deeper content at the start but then the complexity of the concepts increased too fast and I couldn’t keep up with the course. There were also typing errors in the code.
  • The course is nicely structured but once I completed the course I realized it is not particularly targeted towards all types of learners. Meaning, the course is very difficult for a complete beginner. But at the same time, an experienced individual wouldn’t gain much from this course.

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Published by
TTC Team
3 years ago

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