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Opiniones y comentarios de aprendices correspondientes a Managing Data Analysis por parte de Universidad Johns Hopkins

2,940 calificaciones
412 reseña

Acerca del Curso

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
Aspectos destacados
Helpful quizzes
(3 reseñas)
Well-organized content
(24 reseñas)

Principales reseñas

28 de feb. de 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.

22 de nov. de 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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376 - 400 de 408 revisiones para Managing Data Analysis

por Enrique G

29 de jul. de 2020

Too theoretical. The lecturer shares a lot of knowledge and documents the course in good, well-structured text. But it's all too theoretical and not really engaging seeing the same lecturer just reading the theory.

por Christina W

31 de ene. de 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.

por SJ H

17 de may. de 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.

por Matthew B

21 de abr. de 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.

por Kamil P

16 de nov. de 2016

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

por Joe Y

3 de jun. de 2018

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

por Jose C O B

7 de ago. de 2016

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

por Alex F

30 de ene. de 2018

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

por Sona L

20 de oct. de 2015

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

por Julian P

18 de may. de 2020

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

por Suzen C

19 de oct. de 2015

Lecture component not as concise or well edited as expected.

por Enzo D

9 de abr. de 2020

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

por Sebastian C

2 de jul. de 2019

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

por Marc B

17 de sep. de 2016

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

por Ruchit G

12 de abr. de 2018

More case study to relate will be very useful

por JFW

13 de jul. de 2016

Concise overview. Worthwhile introduction.

por Deepak G

28 de jun. de 2016

Very short. Quality of the course is OK.

por Boris L

5 de oct. de 2015

Not much substance to take from this.

por Daniel R D

27 de sep. de 2019

Many very useful information.

por Weihua W

18 de ene. de 2016

Too abstract, too expensive.

por Mohamed T K

26 de jun. de 2020

Good,but boring slightly

por Tristan C

16 de may. de 2020

Ok but a bit light.


17 de sep. de 2017


por Andre R

28 de nov. de 2016

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

por Marcelo H G

14 de jul. de 2017

MIssing real management stuff. Where is project management knowledge? It is superficial in management side, really.