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Johns Hopkins University

Exploratory Data Analysis

Johns Hopkins University via Coursera


In this 1-hour long project-based course, you will learn exploratory data analysis techniques and create visual methods to analyze trends, patterns, and relationships in the data. By the end of this project, you will have applied EDA on a real-world dataset.

This class is for learners who want to use Python for applying data visualization and data analysis, and for learners who are currently taking a basic machine learning course or have already finished a machine learning course and are searching for a practical data visualization and analysis project course. Also, this project provides learners with basic knowledge about exploratory analysis and improves their skills in creating maps which helps them in fulfilling their career goals by adding this project to their portfolios.

Taught by

Roger Peng



3.9 rating, based on 39 Class Central reviews

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  • Life is Study

    Life is Study completed this course.

    The first 2 weeks of the course provide a thorough overview of plotting in R using the base graphical package, the lattice package and the ggplot2 package. Week 3 takes a sudden detour into data clustering and the fairly advanced topics of principal components...
  • Prose Simian completed this course, spending 4 hours a week on it and found the course difficulty to be hard.

    A painful, dull offline course on plotting & clustering in R slapped online with minimal conversion like the rest of JHU's execrable Data Science specialisation*. Hard only due to the appalling pedagogy. (Have these guys heard of labs? Apparently not...)

    *Which, tragically, is apparently one of Coursera's top moneyspinners. Sigh.
  • Anonymous

    Anonymous completed this course.

    Another boring course you'll have to slog through. It's half learning a few things about making plots, half topics that been better covered elsewhere (k-mean). You can actually graduate those courses with horrible programming. As usual you'll learn more by surfing stack-overflow than by the videos. I've done half the assignments before looking at the vids.
  • Anonymous

    Anonymous is taking this course right now.

    A boring and pointless money-generating vehicle from JH. And yes - reviews should be at least 20 words - I wonder if I find a way around that.
  • Brandt Pence

    Brandt Pence completed this course, spending 3 hours a week on it and found the course difficulty to be easy.

    This is the fourth course in the Data Science specialization. The course covers exploratory analyses in R, primarily making figures using the three most common packages: base R, lattice, and ggplot2. The instructors also manage to throw hierarchical clustering,...
  • Jason Michael Cherry completed this course, spending 4 hours a week on it and found the course difficulty to be hard.

    This is a good starting point for any data analysis work, and the course covers the basics, and a bit more, rather well. It's a bit light on what you should do with the information you gather from your data exploration though.
  • Michal
    The course is a part of very good 'data science with R' program (don't know current name cause it changes) available at Coursera.

    The program is quite massive, it contains about 8 courses but is really thorough and well presented. It is designed with even complete beginners in mind, so may start it without any prior knowledge.
  • Markus Stenemo

    Markus Stenemo completed this course.

    Quite good, quite basic for those who want to review their knowledge. Should be good for those with no previous experience.
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    Bill Seliger

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