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Opiniones y comentarios de aprendices correspondientes a Data Science in Real Life por parte de Universidad Johns Hopkins

2,315 calificaciones

Acerca del Curso

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: Course cover image by Jonathan Gross. Creative Commons BY-ND
Aspectos destacados
Statistics review

(44 reseñas)

Principales reseñas


19 de ago. de 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.


11 de nov. de 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 de 280 revisiones para Data Science in Real Life

por Gowtham V

2 de may. de 2020

Would like to have simpler examples to understand some of the concepts.

por Amal L C

16 de mar. de 2017

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

por Victor M R G

1 de nov. de 2021

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

por Poon F

30 de ene. de 2018

This class has more useful materials than previous ones.

por Manas B

10 de may. de 2016

Relevant materials, but lecture delivery is rather dry,

por Matej K

1 de may. de 2018

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

por Angelina

2 de abr. de 2019

The material is too long and boring.

por Weihua W

18 de ene. de 2016

Too short, too expensive.

por Tamara G

7 de jun. de 2020

Technical vocabulary

por Yuvaraj B

26 de dic. de 2017

Very Good Content

por Mohammed R

5 de ago. de 2020


por Francisco

21 de jun. de 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.

por Aline O

17 de jul. de 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.

por Jean-Gabriel P

10 de ago. de 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.

por UMUT R A

20 de jun. de 2020

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

por Karun T

28 de feb. de 2017

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

por Massimiliano T A

31 de dic. de 2020

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

por Marcelo H G

29 de jul. de 2017

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

por Julià D A

13 de jun. de 2017

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

por Shafeeq I

8 de ene. de 2019

Not that engaging content.Too much theoretical approach.

por Peter P

20 de jun. de 2016

Too much focus on technicalities - not management based.

por Hiteshwar G

5 de ene. de 2018

The content and examples seem irrelevant.

por Varun M

19 de sep. de 2016

very boring videos.

por GIacomo V

28 de feb. de 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.

por Kevin K

12 de jun. de 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.