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學生對 约翰霍普金斯大学 提供的 生活中的数据科学 的評價和反饋

2,314 個評分


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
Statistics review

(44 條評論)




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.



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.


251 - 生活中的数据科学 的 275 個評論(共 280 個)

創建者 Gowtham V


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

創建者 Amal L C


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

創建者 Victor M R G


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

創建者 Poon F


This class has more useful materials than previous ones.

創建者 Manas B


Relevant materials, but lecture delivery is rather dry,

創建者 Matej K


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

創建者 Angelina


The material is too long and boring.

創建者 Weihua W


Too short, too expensive.

創建者 Tamara G


Technical vocabulary

創建者 Yuvaraj B


Very Good Content

創建者 Mohammed R



創建者 Francisco


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.

創建者 Aline O


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.

創建者 Jean-Gabriel P


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.

創建者 UMUT R A


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

創建者 Karun T


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

創建者 Massimiliano T A


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

創建者 Marcelo H G


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

創建者 Julià D A


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

創建者 Shafeeq I


Not that engaging content.Too much theoretical approach.

創建者 Peter P


Too much focus on technicalities - not management based.

創建者 Hiteshwar G


The content and examples seem irrelevant.

創建者 Varun M


very boring videos.

創建者 GIacomo V


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.

創建者 Kevin K


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.