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Learner Reviews & Feedback for Data Science in Real Life by Johns Hopkins University

4.4
stars
2,287 ratings
276 reviews

About the Course

Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The conclusions were clear and actionable decisions were obvious. Has that every happened to you? Of course not. Data analysis in real life is messy. How does one manage a team facing real data analyses? In this one-week course, we contrast the ideal with what happens in real life. By contrasting the ideal, you will learn key concepts that will help you manage real life analyses. This is a focused course designed to rapidly get you up to speed on doing data science in real life. 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 “perfect” data science experience 2. Identify strengths and weaknesses in experimental designs 3. Describe possible pitfalls when pulling / assembling data and learn solutions for managing data pulls. 4. Challenge statistical modeling assumptions and drive feedback to data analysts 5. Describe common pitfalls in communicating data analyses 6. Get a glimpse into a day in the life of a data analysis manager. The course will be taught at a conceptual level for active managers of data scientists and statisticians. Some key concepts being discussed include: 1. Experimental design, randomization, A/B testing 2. Causal inference, counterfactuals, 3. Strategies for managing data quality. 4. Bias and confounding 5. Contrasting machine learning versus classical statistical inference Course promo: https://www.youtube.com/watch?v=9BIYmw5wnBI Course cover image by Jonathan Gross. Creative Commons BY-ND https://flic.kr/p/q1vudb...
Highlights
Statistics review
(44 Reviews)

Top reviews

SM
Aug 19, 2017

A very good and concise course that helps to understand the basics of the Data Science and its applications. The examples are very relevant and helps to understand the topic easily.

ES
Nov 11, 2017

Highly educational course on the realities of data analysis. Many good tips for your own analyses as well as for managing others responsible for coherent and accurate analyses.

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251 - 275 of 279 Reviews for Data Science in Real Life

By Amal L C

Mar 16, 2017

It was quite hard with all the statistical jargon. Too much theory.

By Victor M R G

Nov 1, 2021

C​urso entretenido, aunque algo ligero en la parte conceptual.

By Poon F

Jan 30, 2018

This class has more useful materials than previous ones.

By Manas B

May 10, 2016

Relevant materials, but lecture delivery is rather dry,

By Matej K

May 1, 2018

Sometimes it was hard to understand what's going on.

By Angelina

Apr 2, 2019

The material is too long and boring.

By Weihua W

Jan 18, 2016

Too short, too expensive.

By Tamara G

Jun 7, 2020

Technical vocabulary

By Yuvaraj B

Dec 26, 2017

Very Good Content

By Mohammed R

Aug 5, 2020

Good

By Francisco

Jun 21, 2020

The lecturer seems afraid of the camera and the feedback on the quizzes should be better. Also, the summary readings should have all the information in the presentations, so you can check up everything more easily in one place.

By Aline O

Jul 17, 2019

This course for me was the most difficult to understand. Using as example situations with health area was hard to understand how I can apply in my case. But in general, the other courses were very nice for me.

By Jean-Gabriel P

Aug 10, 2017

OK content but delivery could be better. Also poor value for money (you pay 49$ for a course you can finish in a few days) versus other Coursera courses that get you much more bang for your buck.

By UMUT R A

Jun 20, 2020

worst course in executive data science specialization, hard to understand concept. specific examples on health researchs are not common to understand

By Karun T

Feb 28, 2017

The content was redundant at times, at other the dots that were trying to be connected were to wide apart on the spectrum

By Massimiliano T A

Dec 31, 2020

I expected this course to be more practical and with more business example

By Marcelo H G

Jul 29, 2017

It is good but demands statistics and some knowledge in research area.

By Julià D A

Jun 13, 2017

Too qualitative, I would had liked some hands-on examples.

By Shafeeq I

Jan 8, 2019

Not that engaging content.Too much theoretical approach.

By Peter P

Jun 20, 2016

Too much focus on technicalities - not management based.

By Hiteshwar G

Jan 5, 2018

The content and examples seem irrelevant.

By Varun M

Sep 19, 2016

very boring videos.

By GIacomo V

Feb 28, 2016

The course tests are at times partially unrelated to the content of the lessons. In the test of Lesson 7 we are asked if removing jargon from an analysis makes the analysis clearer. This is never mentioned in the course.

The question does not have a unique yes/no solution. It depends on the context, in particular on the audience of the analysis and report. If I'm talking to technical people who knows a lot about the topic jargon can be useful, on the other hand if jargon is not documented it can be confusing.

How are we supposed to know this?

This is just one example, but all the courses of the EDS specialisation had these issues. I don't know if it is a language barrier or what but I feel that I didn't have a chance to study more to get a better score. You either happen to have the same idea of the teacher or you don't, and this is not professional.

By Kevin K

Jun 12, 2020

The course content is good, but there were no instructions how to complete the capstone in order to obtain a certifiate. This was really disappointing after completing the course work. Eventually, I just stopped my subscription.

By Deleted A

Aug 10, 2016

Was expecting soo much more from the entire courses. Not a single practical part, soo much talk and write.

Sorry would not share the course with friends, 190€ is too much for what I have just learned.