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Learner Reviews & Feedback for Managing Data Analysis by Johns Hopkins University

3,282 ratings

About the Course

This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results. This is a focused course designed to rapidly get you up to speed on the process of data analysis and how it can be managed. Our goal was to make this as convenient as possible for you without sacrificing any essential content. We've left the technical information aside so that you can focus on managing your team and moving it forward. After completing this course you will know how to…. 1. Describe the basic data analysis iteration 2. Identify different types of questions and translate them to specific datasets 3. Describe different types of data pulls 4. Explore datasets to determine if data are appropriate for a given question 5. Direct model building efforts in common data analyses 6. Interpret the results from common data analyses 7. Integrate statistical findings to form coherent data analysis presentations Commitment: 1 week of study, 4-6 hours Course cover image by fdecomite. Creative Commons BY
Helpful quizzes

(3 Reviews)

Well-organized content

(24 Reviews)

Top reviews


Feb 28, 2017

A long course compared to others in the specialization, but a lot of great material. Very well presented, the instructors know how to present this material and make it easy to grasp and understand.


Nov 22, 2016

The course is full of the cases and the real life examples coupled with the theory background. Its very simple to understand and the course will definitely be of an value for people looking for

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426 - 450 of 459 Reviews for Managing Data Analysis

By Christina W

Jan 31, 2018

It would be nice to have listed points or tables to summarise/compare context.

As well, it would be good to introduce example separately rather than mixing with the explanation of subject.


May 17, 2020

If you are not extremely careful, Professor Peng will absolutely deflate your enthusiasm towards data science. That is as pleasant as I can be. Otherwise it's good learning material.

By Matthew B

Apr 21, 2016

Didn't get much into the managerial aspect of a data analysis. Instead, it covered best practices for conducting a data analysis. Not the same thing and a little disappointment.

By Kamil P

Nov 16, 2016

It is quite general, I liked the examples, although there could be more varied examples from many other dissimilar disciplines.

By Joe Y

Jun 3, 2018

The questions can get a little too wordy. Find the questions difficult to follow after reading the entire length.

By Jose C O B

Aug 7, 2016

I think these courses need to be condensed into a single one as the contents are rather limited individually.

By Pablo S

Apr 19, 2021

will like more examples detail to understand the plots more interpretation instead generation examples

By Alex F

Jan 30, 2018

Good baseline - might be hard to follow for someone who has not been working the DS Specialization

By Sona L

Oct 20, 2015

Too theoretical for my needs but gives a good background to how to approach analytics.

By Julian P

May 18, 2020

too much time between the videos and the related questions to the videos

By Suzen C

Oct 19, 2015

Lecture component not as concise or well edited as expected.

By Enzo D

Apr 9, 2020

The course is good, but too general and a little boring :(

By Sebastian C

Jul 2, 2019

The videos are to long, but the content is great.

By Marc A B

Sep 17, 2016

Lot of talking, lack of visual, templates, etc.

By Ruchit G

Apr 12, 2018

More case study to relate will be very useful


Jul 13, 2016

Concise overview. Worthwhile introduction.

By Deepak G

Jun 28, 2016

Very short. Quality of the course is OK.

By Boris L

Oct 5, 2015

Not much substance to take from this.

By Daniel D

Sep 27, 2019

Many very useful information.

By Weihua W

Jan 18, 2016

Too abstract, too expensive.

By Mohamed T K

Jun 26, 2020

Good,but boring slightly

By Tristan C

May 16, 2020

Ok but a bit light.


Sep 17, 2017


By Albert P

Jan 27, 2022

Approaches the topic from a perspective that's too academic and pedantic for working professionals. Practical, useful insights are low. The frameworks presented here just don't seem very useful and end up making data analysis seem more confusing than it really is.

By Andre R

Nov 28, 2016

Not as I expected. More readings than practices/exercises. Seems more target on traditional statistics than machine learning.