Chevron Left
Вернуться к Managing Data Analysis

Отзывы учащихся о курсе Managing Data Analysis от партнера Университет Джонса Хопкинса

4.5
Оценки: 2,198
Рецензии: 292

О курсе

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...
Основные моменты
Well-organized content
(рецензий: 24)
Helpful quizzes
(рецензий: 3)

Лучшие рецензии

EL

Mar 01, 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 23, 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

Фильтр по:

251–275 из 287 отзывов о курсе Managing Data Analysis

автор: George K

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!

автор: Alok B

Aug 05, 2018

Need some project work

автор: Rudy d P

Oct 14, 2018

very insightful

автор: Brenden M

Apr 21, 2019

V

e

r

y

c

h

a

l

l

e

n

g

n

g

c

o

u

r

s

e

,

w

o

r

t

h

e

v

e

r

y

s

e

c

o

n

d

s

p

e

n

t

o

n

I

t

автор: Amit J

May 14, 2019

Good communication

автор: Jose C O B

Aug 07, 2016

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

автор: Augustina R

Dec 29, 2016

Content could have been boiled down to about 3 lectures. Most of it was common sense. The high level over view of the life cycle of data analysis projects was interesting and overall this was a good introduction to the field.

автор: Siddharth M

Mar 26, 2017

The course was very informative but the slides were a little boring. The content could have been more engaging. Sometimes the supplementary reading contained examples that could have been better explained in a video. I would have appreciate a more comprehensive explanation of content on slides using markers or pointers. Sometimes I did not know where I needed to focus. I hope the instructors create more videos for the same content. This is may be because I am more of a visual or an engaged learner.

автор: Suzen C

Oct 20, 2015

Lecture component not as concise or well edited as expected.

автор: JFW

Jul 13, 2016

Concise overview. Worthwhile introduction.

автор: 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.

автор: Deepak G

Jun 28, 2016

Very short. Quality of the course is OK.

автор: Deleted A

Nov 02, 2016

Lots of talking head videos without enough visual aids to solidify the adult learning process. Not very "Executive level" as the course title and description imply. I would expect more "TED Talk" level lectures and materials, with plenty of real-world examples. Content in these courses seem more "new manager / new supervisor" level, if not actually geared toward an undergrad audience.

автор: 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.

автор: Marc B

Sep 17, 2016

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

автор: Boris L

Oct 05, 2015

Not much substance to take from this.

автор: Joe Y

Jun 03, 2018

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

автор: Christina W

Feb 01, 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.

автор: Alex F

Jan 30, 2018

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

автор: TCSONG

Sep 17, 2017

不推荐没有实际经验的人学

автор: Weihua W

Jan 19, 2016

Too abstract, too expensive.

автор: Deleted A

Aug 08, 2016

Personally not a big fan of Roger Peng's approach while teaching. The lessons get a bit confusing, and so does the questions from the quiz.

Jeff Leek's approach is more calm and simple.

Nevertheless, the course in general is really good.

автор: Sona L

Oct 20, 2015

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

автор: Ruchit G

Apr 12, 2018

More case study to relate will be very useful

автор: Hana P

Jul 21, 2019

If only the course lasted a little bit longer... for those who wish to complete the course as soon as possible, this is the course you should take otherwise i personally find it hard to get the idea of what really "managing data analysis" means other than its basic concepts and models/ trends etc.