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學生對 约翰霍普金斯大学 提供的 探索性数据分析 的評價和反饋

4.7
5,978 個評分
874 條評論

課程概述

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data....

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Y

2017年9月23日

Very good course! It provide me the foundation in learning how to plot and interpret data. This will definitely strengthen my "R programming" to generate publication type figure for my genomics data!

CC

2016年7月28日

This is the second course I have taken from Roger Peng and both were outstanding. I have a strong math background, but not much of a background in stats, but this course was very approachable for me.

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626 - 探索性数据分析 的 650 個評論(共 843 個)

創建者 naghma q

2020年12月17日

Enjoyed this course a lot. This course allowed me to experiment with and practice various plotting techniques while analyzing the data in the initial stages. SVD and PCA were totally new concepts to me. It would have been better to see some real examples from the field with interpretations instead of understanding these concepts using random numbers' examples.

創建者 claire b

2019年9月10日

Course gives thorough introduction to basic tools for exploratory data analysis, including visualisation, PCA and clustering. Good mix of lectures, practical in swirl and programming assignment. Swirl practice are mostly a repetition of the examples in the presentations, which is a bit of a pity...and I missed a programming assignment on cluster analysis/PCA

創建者 Kalle H

2017年11月27日

Very good. Great videos but perhaps the most learning was obtained through seing different apparoches taken during the peer review. The course could be even better if more smaller peer reviewed tasks where to be completed where extra points where rewarded for not just displaying correct data, but also visualising it more efficiently.

創建者 Doaa E

2020年2月18日

I'm glad for completing this course, it added a value for me.

I wish the videos about (SVD and PCA) in week 3 was more clear but it was difficult for understand and i feel lost , I think you need to update this videos to have more a satisfied materials.

Thanks for your effort and for what i have learned for this course

創建者 Zhang S

2018年7月9日

Week 3 content is difficult to understand without background knowledge in clustering and component analysis. Hope the instructor can provide some materials or web links for cluster and component analysis at the beginning of Week 3. Other weeks' contents are good and helpful!

創建者 STEVEN V D

2017年12月7日

Great practical course on exploring big datasets in R. The main part, plotting, is very clearly and thoroughly explained and framed. Only 'single value decomposition' and 'principal components analysis' was somewhat hard te grab and need a lot of extra research and study.

創建者 Glenn W

2019年3月2日

I really enjoyed this course. I was a good reminder of what analysts need to do when looking at a new dataset. Dr. Peng does a great job walking through the steps and there is enough information given to enable the student to effectively explore on their own.

創建者 Jacques K

2020年6月16日

The course was really good, thanks for that; however the part of single value decomposition and principal components analysis was not explained in a gradual fashion and even though I researched outside of the course I still have some confused concepts there.

創建者 Ryan B

2018年4月25日

Good, but the lack of assignment in week 3 seemed to screw up the UI, prompting me continually to do the Swirl exercises, which were non-compulsory (and, given I hadn't completed any of the other Swirl exercises, something I didn't want to take on.)

創建者 Guilherme B D J

2016年6月9日

The only missing point I would say about this course is how to deal with skew data and/or outliers. Although it is not specific to "cleaning data", I think there is a good opportunity there to at least give some hints on this subject

創建者 Rashaad J

2017年8月28日

The Swirl activities followed along with the lectures, which allowed us (as learners) to better understand core concepts. The lecture videos continue to end while the professor is still speaking, but this is not a major issue.

創建者 Ashish S

2017年4月1日

It was awesome to learn visualization. SVD and PCA part of the course could have been elaborated better, and a pilot project on that would have cleared the basic concept. As usual Prof. Roger is a engaging and amazing teacher.

創建者 Mark F

2018年3月27日

The course was great, I'm not sure if I'd really consider using the base plotting package in reality as the plots are just too ugly, and the API is harder to learn. I think a stronger on ggplot would help to keep it relevant.

創建者 Connor G

2017年8月14日

I enjoyed the course and learned important graphing concepts for R/RStudio. I just wish the assessments had been a little more rigorous, as it felt like I could have done better but still passed the projects anyway.

創建者 Greg A

2018年2月22日

This is a very good course, at times it felt like the instruction was to do things mechanically without understanding the motivation. Perhaps this should come after or in conjunction with Statistical Inference

創建者 caramirezal

2017年5月28日

I love the course. However, the treatment of PCA, SVD, and colors seems to me very long and slow. Maybe a more direct and quick overview would be better. Even with that expection I really enjoy the course.

創建者 Ben K

2020年12月27日

It was fun and interesting learning how to explore the data. For the final project I missed a assignment about clustering, PCA and SVD. It could be useful for a better understanding of the concepts.

創建者 Bill S

2017年6月21日

The course on Exploratory Data Analysis was highly enjoyable. I used to do a lot of this sort of thing in my job, but now spend more of my time managing people. It is fun to get "hands-on" again.

創建者 Jukka H

2020年6月14日

Great in-depth content about techniques related to exploratory data analysis and implementation in R language using R Studio. Definitely recommend this course to any aspiring data scientist!

創建者 Raviprakash R S

2017年2月13日

Nice course, but too much focus on "R" as a tool.... Industries don't use R as much... The course must be made more generic and independent of R - understand it is not easy to do but ....

創建者 Luke S

2019年10月31日

Good introduction. The swirl exercises kind of reproduce the lectures though- felt like it might not have been the most efficient use of time to go over the exact same example again.

創建者 Bo L N

2017年3月9日

When it comes to hierarchical and K-means clustering, the theory wasn't explained clearly. When do we use U and V for what purpose? How does D come in? I'm left confused after this.

創建者 Štefan Š

2016年4月17日

I found it very useful.

Some space for improvement are better coding skills (naming variables) and

some more complex topics like SVD / PCA should be explained in a more intuitive way.

創建者 Diego P

2018年1月7日

It's a very good course. Week 3 was a little bit more challenging than expected, as well as assignment 2, but you get a good idea of how to use all the different plotting systems

創建者 Christian B

2016年12月11日

The course is interesting and the content is relevant. I do think that there are some issues with project 2 though. I did provide feedback on that to the course administrators.