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學生對 约翰霍普金斯大学 提供的 可重复性研究 的評價和反饋

4.6
4,113 個評分

課程概述

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available. This course will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results....

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AA

2016年2月12日

My favorite course, at least it gives me an argument why scripted statistics is awesome and can be applied to a number of data related activities. Recycling chunks of code has proven useful to me.

RR

2020年8月19日

A very important course that greatly improved my ability to communicate the findings of any sort of data analysis that I perform. This is a critical skill to acquire to "deliver the means."

篩選依據:

51 - 可重复性研究 的 75 個評論(共 580 個)

創建者 Angela W

2017年9月15日

Despite this being the course with the lamest name (sorry), I really enjoyed it! I learned a lot of new stuff and also got to apply the things that I learned in the previous courses (especially Exploratory Data Analysis), so I feel that this was time well spent.

創建者 Deleted A

2018年9月21日

The course was fantastic. I realized the power that a Data Science Analyze can create. In this module in particular, I was even more interested in completing the specialization. Thank you Professor Roger Penn and the entire team of teachers for their teachings.

創建者 Arindam M

2017年3月20日

A great course which might not draw the right attention while moving towards a data scientist role. But without a great deal of focus on the communication of analysis is even more important to gain buy-ins within or outside the org. Will keep them in mind.

創建者 Scipione S

2020年6月7日

Wonderful course. Maybe you could enlarge the part related on litarate programming, and you could change the position in Data Science Specialization. I also think, it would be better to arrange it after Statistical Inference and Regression Models courses.

創建者 Eduardo A

2017年2月10日

This course makes us re-think things that we take for granted. I was shocked in the beginnig on how we ignore practices that should be the basics of any research. As the course progress, I learned new concepts what is essential to our self development.

創建者 Arunkumar M R

2017年9月11日

I guess from the case studies and research on the web whats I learned from this course is the importance of reproducible research is. This course explains the importance of it and the ways to achieve it easily and concisely. Thanks for the authors.

創建者 Dan K H

2016年4月11日

This turned out to be one of the more fun courses, especially listening to Rogers lecture "live in class room" and also the case presented by M.D. Anderson was great. I really enjoyed this course, even more than I initially expected to.

創建者 Lowell R

2016年10月7日

This is an excellent course which teaches you fundamental best practices in research. After completion you will look back at early scripts in horror! It's unfortunate that the practices you learn aren't more widely practiced.

創建者 Ray L J

2017年5月2日

My favorite course in the degree, so far! I started applying what I learned immediately. This course should be mandatory for any data analyst, as the concepts are applicable no matter which language or tools are used.

創建者 坂本幹次

2020年9月29日

There are important things you usually dismiss.

The lecture is great and it really deserve professional course.

This lecture is potentially hard, so you should spend a lot of time for the lessons and course projects.

創建者 Jordan I

2020年1月8日

Great course that provides a structure for analysis and how to challenge the analysis. I found the assignments hard. The lack of information about the data for the assignment represented a real-life situation.

創建者 Jorge B S

2019年8月20日

I have found this course very useful in order to learn the keys of reproducible research. Moreover, both course projects are useful for putting other skills of this specialisation into practice. I recommend it!

創建者 Regis O

2016年8月29日

This course had a profound impact on the procedures I use for data analysis. It provides best practices for documenting the steps of the analysis to ensure accuracy and quality. I highly recommend taking this.

創建者 James S

2016年5月21日

This has been a great introductory course into reproducible research. The topics were clearly carefully chosen and wisely integrated to create a smooth flow. Money well spent and invaluable knowledge gained!

創建者 Marco A M A

2016年3月8日

It is a nice introduction to some important issues in scientific research, may not be so intresting to non academic data scientist hopefuls, but it is very important, I think to those that are within academia.

創建者 Rumian R

2020年8月20日

A very important course that greatly improved my ability to communicate the findings of any sort of data analysis that I perform. This is a critical skill to acquire to "deliver the means."

創建者 Alán G

2019年5月2日

A very useful course. It helped me to improve the way I structure the analysis at my current job, especially by keeping track of every transformation I apply to the data I’m working with.

創建者 Araks S

2017年6月23日

Of course, I liked this course. There was even an extra non-graded assignment. Plus two graded assignments. Quality instruction videos and lots of practice. Everything a learner needs.

創建者 Mikael F

2022年3月31日

I took this course as part of the Data Science specialization without any real expectation and realized that this subject is probably one of the most important in data analysis.

創建者 Chetan T

2019年4月22日

This course is very helpful in terms of not only doing the analysis but also getting to know the finer nuances of making a structured markdown document for future reproducible.

創建者 Ramesh G

2020年4月30日

Great topic which is discussed well with a good case study. I'd like to see more up-to-date content and more detailed analytical techniques. However, it's a nice introduction!

創建者 Ryan H

2017年8月21日

I personally got a lot out of this, both from a philosophical perspective and a nuts-and-bolts perspective. And I got to practice a lot of stuff learned on earlier courses.

創建者 Luis T

2022年7月21日

This course provides the necessary resources to learn how to do good science, what is reproducibility and few guidelines about how to write a good report using RMarkdown.

創建者 Dylan E

2017年8月5日

Very informative and enjoyable class. The importance of reproducible research is stressed clear and concisely, Roger D. Peng does a great job of explaining the material.

創建者 Vishwamitra M

2020年2月14日

Highly recommended for beginners to learn the basics of Data Science, Re-producibility and how to write a good report around the analysis done by you as a data analyst.