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University of California, San Diego

Hadoop Platform and Application Framework

University of California, San Diego via Coursera


This course is for novice programmers or business people who would like to understand the core tools used to wrangle and analyze big data. With no prior experience, you will have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment. In the assignments you will be guided in how data scientists apply the important concepts and techniques such as Map-Reduce that are used to solve fundamental problems in big data. You'll feel empowered to have conversations about big data and the data analysis process.


  • Hadoop Basics
    • Welcome to the first module of the Big Data Platform course. This first module will provide insight into Big Data Hype, its technologies opportunities and challenges. We will take a deeper look into the Hadoop stack and tool and technologies associated with Big Data solutions.
  • Introduction to the Hadoop Stack
    • In this module we will take a detailed look at the Hadoop stack ranging from the basic HDFS components, to application execution frameworks, and languages, services.
  • Introduction to Hadoop Distributed File System (HDFS)
    • In this module we will take a detailed look at the Hadoop Distributed File System (HDFS). We will cover the main design goals of HDFS, understand the read/write process to HDFS, the main configuration parameters that can be tuned to control HDFS performance and robustness, and get an overview of the different ways you can access data on HDFS.
  • Introduction to Map/Reduce
    • This module will introduce Map/Reduce concepts and practice. You will learn about the big idea of Map/Reduce and you will learn how to design, implement, and execute tasks in the map/reduce framework. You will also learn the trade-offs in map/reduce and how that motivates other tools.
  • Spark
    • Welcome to module 5, Introduction to Spark, this week we will focus on the Apache Spark cluster computing framework, an important contender of Hadoop MapReduce in the Big Data Arena. Spark provides great performance advantages over Hadoop MapReduce,especially for iterative algorithms, thanks to in-memory caching. Also, gives Data Scientists an easier way to write their analysis pipeline in Python and Scala,even providing interactive shells to play live with data.

Taught by

Natasha Balac, Paul Rodriguez and Andrea Zonca


1.9 rating, based on 25 Class Central reviews

4 rating at Coursera based on 3318 ratings

Start your review of Hadoop Platform and Application Framework

  • Nancy Demir
    I am enrolled and almost done with this course. I cannot wait to get done! I have taken many other courses on Coursera, and this one is the worst. I do not feel that it is giving me a true sense of what Hadoop or big data is all about, nor…
  • Definitely better than the "Introduction to Big Data", but still miles away from what I consider a decent course. What's the point in presenting slides and reading the keywords to students? What's the point in handing out those slides instead of "real" documents (compare the ideas of Garr Reynolds or Nancy Duarte on that issue)? What's the point in testing for simple facts? On the bright side: The hands-on assignments were kind of fun, although I fear some people may get frustrated as some background in programming definitely helps - should be made clear in the syllabus, I think.
  • Victor Pillac
    Very poor course, the lectures are not structured and presetend in an interesting way, while the quizes test for simple facts.
    The lecturer (Dr. Mahidhar Tatineni) reads the bullet points or a script, and repeats a lot of what was said in the previous course from the specialization.
    Not worth my time, and definitely not worth the price if you are considering doing the specialization.
  • Profile image for Gerrit Klaschke
    Gerrit Klaschke
    I felt I was tricked into this specialization. Not much content, lots of repeats. Definitely not worth the money. $10, ok. but no penny more. I dropped out and got a refund.
    Most troubling is the lack of responses from Coursera staff and UCSD lecturers. Silence from all sides.
  • Anonymous
    This course Sucks, only slides and slides.. nothing useful, I recommend you look for another options if you want to learn about big data.
  • Anonymous
    The Course videos are poor in content and in explaining what the tools do. The Quizzes ask questions that have not been covered in the video material and the programming assignments are in many cases unrelated to what is explained in the videos, ins…
  • Sam K
    Very poorly delivered course. I have some exposure to Hadoop and thought this course would give a full stack in-depth hands on experience as this is a total 7 months specialization. But dropped out and was lucky to get a refund. Very superficial coverage of the course and very poorly delivered. The presenters just read from a poorly prepared slide content.
  • Brian O.
    The course is presented by 2 lecturers at UCSD. The Hadoop lectures were bullet points recited from Powerpoint slides. The required assignments presume working knowledge of Python that was not disclosed prior to enrollment. The Spark lectures were abysmal; none of the bullet points recited were explained or expounded upon. I would not recommend this class to anyone.
  • Profile image for Pablo Torre
    Pablo Torre
    The quality of the course is not very high.

    The quizzes are painful with correct answers being counted as wrong and "choose all that are true" format questions that provide no feedback. For the most part they tested for "facts" and memory retention.

    However, it does provide a good overview of the different components in the Hadoop ecosystem, and did provide a good guidance for further studies into these tools.
  • Kumar NP
    I am almost done with this course. Thouroughly disappointed with the course content. It is too basic and high level. I have exposure to hadoop, reason for taking this course was to gain structured knowledge at least at an intermediate level, which did not happen. Lecturers just readout the slides, no insight into any of the content.
  • Anonymous
    It is a beginner course, so has to be valuated as is. It help the student to know the basic tools and concepts in the hadoop eco system. Quizzes are good if taken seriously and you really understand if you grasp the concepts. Was one of the first course online that I take, so I have no terms to compare to, but yes, it is absolutely missing some interaction with the tutors.
  • Anonymous
    One of the worst courses I have taken.
    Don't waste your time. My head was filled with the Hadoop stack and what I need is Map and reduce the information this course provides. A lot of slides without pointing out the essence.

  • It's a joke of course. Take some other course not Coursera San Diego. The course team DO NOT PUT any hours of EFFORT into developing the course. No material, not good examples, not good exercises. The The tech are exercises that later you realize th…
  • Anonymous
    These people might be knowledged, but they teach this course in the worst way possible!! Reading everything from slides is not a good way to teach a concept. I didn’t have patience to continue this course, I have already made a request for refund, I definitely wouldn’t wanna waste $102 for someone that simply reads content from the slides. Udemy has amazing course content for a fairly cheaper price. Goodbye Coursera
  • Anonymous
    Very bad. The instructors obviously did not undergo any type of didactic course before making this course. Made the Udemy Hadoop course afterwards which was better.
  • Anonymous
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