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學生對 卫斯连大学 提供的 数据管理与可视化 的評價和反饋

815 個評分
229 條評論


Whether being used to customize advertising to millions of website visitors or streamline inventory ordering at a small restaurant, data is becoming more integral to success. Too often, we’re not sure how use data to find answers to the questions that will make us more successful in what we do. In this course, you will discover what data is and think about what questions you have that can be answered by the data – even if you’ve never thought about data before. Based on existing data, you will learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly. By the end of the course, you will be able to use powerful data analysis tools – either SAS or Python – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs. Throughout the course, you will share your progress with others to gain valuable feedback, while also learning how your peers use data to answer their own questions....



Jul 16, 2020

In this course we can get many ideas and opportunities of the english and the meaning of many things we used to no many things we should have been working many ideas and then how we should shall have


Jun 11, 2017

This course covers the basic data management and visualization using SAS and Python. I like the simplicity and straightforwardness of the contents. Will continue to explore this specialization.


176 - 数据管理与可视化 的 200 個評論(共 217 個)

創建者 Daniel R C

Nov 23, 2015

Wish they offered R

創建者 vishalini.B

Aug 31, 2020


創建者 Haripriya.s

Aug 31, 2020


創建者 sanskar j

Jul 08, 2020


創建者 ngoduyvu

Feb 16, 2016


創建者 Steven B

Jun 29, 2016

I appreciate the fact that this course doesn't go into the fine detail on how to code everything, I believe there is still more information on the coding and data management practices that could be included in the course content. In addition to that, I feel the course could use the following adjustments to make it better:

1 - Have Python students grade other Python students and SAS students grade other SAS students. While it is nice to get exposure to another language, it is more than enough to learn one at a time.

2 - Add quizes and/or other well formed questions that are graded (automatically, not peer graded) to help enforce the concepts being taught.

3 - Make the assignment instructions/expectations more clear. I feel there are times when the grading criteria don't exactly match the requested assignment. While people follow the spirit of the assignment, the grading questions may ask for slightly different or additional items.

4 - Certain aspects of statistical analysis are glossed over and should be covered in more depth in the training videos. While I like the short videos for brevity, I would prefer to watch 10-15 minutes more content and really feel like the material was well covered.

創建者 Elizabeth C

Aug 06, 2018

Felt like a lot of the lessons were more about just following the directions or structure of the videos and not really learning the actual language of SAS or Python and how to be creative with it. I feel like I know how to use them at this point, but only for the specific commands we were instructed on. However, material is clear and easy to follow. I am not a fan of the overall Coursera structure of peer graded assignments because it seems pretty arbitrary or you may do the work and just not get the right number of reviewers and then you're screwed.

創建者 Nicolas K

Feb 07, 2016

The course has its positives, but overall does not perform well instructing on the use of the two statistical software offered (SAS & Python). At the beginning they offer multiple data sets to use and formulate a research question, but all the examples utilize only one data set and do not cover the differences you might face with the other data sets - leading to a lot of missed opportunities. Additionally, the tutorials for using the statistical software do not lend themselves towards a thorough understanding and more to a route learning.

創建者 Francois R

Jan 20, 2016

The course is a very good introduction to Python for data exploration and management.

That being said, it focuses too much on categorical data analysis, and I felt the transition to quantitative/continuous data was not very well done.

Moreover, some more explanations about several Python functions or coding choices could be better explained.

But it's encouraging to see this type of statistical course for Python and not R!! Again!

創建者 Avinash S

Dec 30, 2016

A decent start for anyone interested in learning the basics. However, please make sure you add extra efforts from your end in understanding stats concepts if you are totally new to the subject as well as browsing things related to usage of SAS or python. The course touches only the basics so it is up the learner to explore and learn more about interested statistical tool.

創建者 Sarah P

Nov 07, 2015

They put a lot of effort into this course, but especially for the videos it was a bit too much. So many different visual backgrounds, sounds, music, text floating it... It's as if they just wanted to use everything, while never thinking about when it would start being too distracting.

創建者 Elma B

Dec 23, 2015

The slides are excellent and instructions are clear and to the point. But that point is very limited. The main negative about this class is that there is absolutely no student/TA/teacher feedback and you're pretty much on your own learning.

創建者 James M

Mar 06, 2016

It was good overall, some of the course materials were a bit sparse. You had to do your own research into getting packages working in spyder etc.

I'd probably recommend that learners learn some python separately and read the docs for pandas.

創建者 Johann Q

Sep 27, 2015

A great idea to create a project based online course. We should focus on application based learning not on lectures. You need improve this course still. 4 weeks are to short.

We need more deep and more weeks.

創建者 Chris B

Nov 23, 2016

It is a good beginners course but I think there are better lessons in SAS and Python if learning these is your goal, and the content in data cleaning and visual analysis is very basic.

創建者 Mark E

Jan 04, 2017

Course content good but a little too basic in my eyes. I think the addition of more functions in SAS/Python would be useful. Having to do peer reviews is also not ideal.

創建者 Markus K

Aug 21, 2017

Nice course to learn Python and some graphing libraries besides doing your own study from real-life data

創建者 ramesh

Oct 06, 2015

good but i thought it will cover most of SAS technology. But it has covered basics only .

創建者 Tiffany P

May 01, 2016

Course material needs to updated to reflect current software updates.

創建者 Jonnatan S C

Mar 04, 2016

Very superficial. Too few in statistics, too much in python and SAS.

創建者 Rong G

May 16, 2018

So many unanswered questions in the forum. Peer reviews suck

創建者 Ponciano R

Jan 10, 2019

The course is good, although it goes a little to fast.

創建者 Aneeshaa S C

Jul 05, 2017

course should've had deeper python content.

創建者 Jessica

Dec 27, 2015

The content is OK, but that's about it. Near zero interaction from staff, short videos leave a lot to be desired, and worst of all, there seems to be a problem getting everyone's assignments peer reviewed (which makes no sense).

There is a somewhat comical thread wherein staff direct students to contact coursera directly via a "contact us" link on a page, but get this, the link isn't there. Students repeatedly pointed this out only to get directed again to the non-existant link. In an online forum it's important to actually address concerns. Replys that avoid directly addressing concerns sound like automated messages. And that's the feeling I get here.

This course requires a DIY attitude and a willingness to proceed without feedback.

If you're looking for a good example of online learning, look elsewhere.

創建者 John F

Jul 13, 2020

Some of the presented python code has been depreciated; this would be particularly challenging for students new to the code. The use of quantitative variables is not well described at the start of the course which would add challenges for students who choose these variables and are marked by students who have not. Having beginners marking beginners is not an effective evaluation technique. I did not receive useful feedback on assignments; typical statements included ".", "good work", and, "needs improvement".