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

4.6
stars
3,305 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 https://flic.kr/p/4HjmvD...
Highlights
Helpful quizzes

(3 Reviews)

Well-organized content

(24 Reviews)

Top reviews

EL

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.

ST

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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326 - 350 of 465 Reviews for Managing Data Analysis

By Christopher L

•

May 1, 2018

Pretty good, but I would have liked more math. I understand that others would not, but many times one equation can cut through 3-4 paragraphs and be more clear than the text. It can be frustrating knowing that if you just had the equation things would be 100% clear, but with just a bunch of text, you just get a vague idea, for more work, ie reading time.

By Abhishek S

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Sep 18, 2017

The course was good but as a suggestion, walkthrough of an example for the modelling would have helped. I was little confused when the equation was used during the course to explain the confounder, predictor and outcome. Instead of using X, Y, Z - may be use an actual example and show they all relate would have made the course

By Christos G

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Aug 29, 2017

Very interesting insights and ideas about how to manage Data Analysis, especially the part with the communication. I think there could be some more emphasis on the troubleshooting side, as it overall appeared to be a finite, engineering process which can always end successfully if the instructions are followed closely.

By Triste R S

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Feb 8, 2017

It was very informative. The instructor needs to slow down just a little though, I could tell he's a little nervous speaking to "large groups". Otherwise, it was great. I'm from BAWA and I am familiar with and love JHU, so I support any great course coming from there.

By Jens P

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Apr 11, 2016

Excellent focus on what makes managing Data Analysis teams different from managing managing other teams. This course has the most impact if combined with general management background/classes. Speech fillers, like "um," "ah," "like," etc. prove distracting at times.

By Carsten K

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Jun 4, 2020

Great course and overview of the processes involved. But it would be great if the readings were also put into videos (I'm doing an online course - if I wanted a book, I would buy it). And please (!!) get rid of the music in some of the videos, as it just distracts.

By JOSEPH A

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Apr 9, 2018

Brilliant course - fantastic overview. What's lacking for 5* is the EDA exercise in R should've been within an R IDE to enable total beginners to get more hands on. After all EDA is mostly about DOING. Hope course designers fix this for the next iteration.

By Cristian F

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Nov 12, 2017

The topics in the course shows that there is a set of steps to counduct a data science project since the definition of the question to solve to the apropiate way to communicate the results. The content of some videos could be considered technical.

By serge a

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Dec 21, 2017

Very valuable, however, in particular the section on inference vs prediction included material not explained before and hard to follow. Also examples with t-values and interpretation of values when adding confounders was difficult to grasp.

By Rorie D

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Apr 18, 2016

Liked how a lot of content was covered in a small amount of time. Thought the instructor was effective in presenting the important elements of the lectures. Only issue is some typos in the quizzes that were a bit distracting.

By Kwame A

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Nov 8, 2017

Great course with short digestible lessons, great lecturer with an ability to communicate technical details in a very engaging manner, and my appreciation of data analysis is better. Am glad I took this course.

By Janusz Z

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Oct 4, 2015

It was a great experience a big amount of knowledge in a short presentation. Overall the summary papers are great, however I missed a more interactive videos with more bullets points and etc.

Thank you!

By Benjamin T C

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Dec 31, 2019

Like other reviewers said, this course is larger than the two previous courses. The content is excellent but I am giving 4/5 stars because I found many misspelled words throughout the course lectures.

By RANJITH D

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Apr 7, 2019

This course is not for a person without any idea of Data analysis or Statistics. This course isn't for beginners. The content could have been presented even better with lucid examples.

By Vipul G

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Jul 26, 2017

Good overview of the process. Helped me in bridging data analysis processes with things that I already do as part of project management or business analytics/decision support projects.

By Jose a z r

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Nov 11, 2015

Critical thinking is essential at the moment of working over data. This was a nice course with a very good theory about all the process,which a data analyst has to perform.

By Kevin C

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Oct 31, 2017

Well defined strategies for getting a handle on the data analysis process. Short and concise class that hit on relevant points required to be successful in this area.

By George K

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Sep 16, 2017

sometime it was not easy to understand the lecturer. also, it would be good to try some things out versus reading the expamples. other than that - a great course!

By Bernard D V

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Mar 19, 2020

A great course with a lot of information. However, the course might be more concise sometimes due to the complexity of the information brought by the instructor.

By Scott K

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Oct 10, 2015

Good course for the fundamentals of making sure data analysis is done correctly. These are good things to keep in mind when you are managing a data science team.

By Prabal T

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Dec 27, 2020

Course is very good and concise from a business owner point of view. Other technical courses will definitely add to the nuances of full fledged insights.

By Kian G L

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Aug 12, 2016

Comprehensive overview to understand activities involved in the iterations and epicycles of Data Analysis and to manage it with correct expectation.

By Victor D R L

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Apr 24, 2020

It is a very good course but challenging, I had to make a lot of notes to understand the concepts and follow the lectures. It is a good investment.

By Deleted A

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Feb 19, 2019

While it was good, a lot of overlapping information and I wish it had more specific examples (rather than theoretical) in public health standpoint.

By Sarah A M A

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Aug 14, 2020

a lot of information, in a short period of time, I think it would be better if they use presentations and graphs and would be more easy to follow