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Managing Data Analysis(으)로 돌아가기

존스홉킨스대학교의 Managing Data Analysis 학습자 리뷰 및 피드백

2,710개의 평가
372개의 리뷰

강좌 소개

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
(3개의 검토)
Well-organized content
(24개의 검토)

최상위 리뷰


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.


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

필터링 기준:

Managing Data Analysis의 367개 리뷰 중 126~150

교육 기관: austin v v

Apr 24, 2018

Another fantastic leg of this course. Clear and precise.

교육 기관: TOSIF M

Mar 04, 2018

Best explanation methodology followed. Best Experience !

교육 기관: Rogelio C G

Jul 19, 2020

Great job! the best course of the specialization so far

교육 기관: Yılmaz M

Jun 06, 2020

If you read this review. you should joined this course.

교육 기관: Muhire I

Sep 30, 2018

Great course and the materials and the tutors are great

교육 기관: Miaojun Z

Oct 20, 2015

Great instructor and helpful course materials! 5 stars!

교육 기관: Alberto D E

May 14, 2018

Just the right depth for a Data Science team manager.

교육 기관: Liz A d S B

Jan 04, 2017

My favorite course from the Specialization until now.

교육 기관: Jennifer L D

Sep 27, 2015

A brisk and effective introduction to data analysis!

교육 기관: Lorenz F

Jan 29, 2018

Great introduction to the process of data analysis!

교육 기관: Ramkumar

Jun 29, 2017

Outstanding course. The lecturer made it very easy

교육 기관: claudio

Sep 26, 2016

Very good balance between content and presentation

교육 기관: Nachum S

Jul 12, 2018

Excellent content, well explained, good use cases

교육 기관: Gayatri A

Jul 14, 2017

Amazing course . Must for all data professionals.

교육 기관: Siddhartha S

Apr 05, 2017

Crisply covered critical aspects of Data Analysis

교육 기관: Hyejin C

Oct 04, 2015

I just love JHU courses. Well-organized and made.

교육 기관: Rhodes B

Sep 07, 2016

Best course in the specialization - thanks team!

교육 기관: Michael F

Jan 18, 2018

excellent easy to follow explainations, thanks!

교육 기관: Kristin C

Sep 11, 2018

Really liked Roger's enthusiasm for the topic!

교육 기관: Ubirajara A T S

Dec 22, 2015

Very good and interesting course, I recommend!

교육 기관: Francesco

Jul 03, 2019

A complete overview in managing data analysis

교육 기관: David S

Nov 02, 2017

Great course about the data analysis process!

교육 기관: RON R C

Oct 21, 2015

Great Discussions from Managing Data Analysis

교육 기관: Juana

Jan 26, 2020

It is very clearly constructed and helpful.

교육 기관: WILLIAM E A

Mar 05, 2019

Não encontrei onde baixar o certificado ...