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 26, 2018
This is a great course for beginners. The course instructors have arranged the course at a very comfortable pace and this is a great beginning point for anyone who wants to learn SAS or Python.
교육 기관: Seho Y•
Nov 26, 2018
It's easy and helpful
교육 기관: Parvathgari A R•
Jun 21, 2016
It was really good.
교육 기관: Daniel R C•
Nov 23, 2015
Wish they offered R
교육 기관: vishalini.B•
Aug 31, 2020
교육 기관: Haripriya.s•
Aug 31, 2020
교육 기관: sanskar j•
Jul 08, 2020
교육 기관: ngoduyvu•
Feb 16, 2016
교육 기관: 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.
교육 기관: 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.
교육 기관: 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.
교육 기관: 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!
교육 기관: 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.
교육 기관: 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.
교육 기관: 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.
교육 기관: 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.
교육 기관: 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.
교육 기관: 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.
교육 기관: 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.
교육 기관: Markus K•
Aug 21, 2017
Nice course to learn Python and some graphing libraries besides doing your own study from real-life data
교육 기관: ramesh•
Oct 06, 2015
good but i thought it will cover most of SAS technology. But it has covered basics only .
교육 기관: Tiffany P•
May 01, 2016
Course material needs to updated to reflect current software updates.
교육 기관: Jonnatan S C•
Mar 04, 2016
Very superficial. Too few in statistics, too much in python and SAS.
교육 기관: Rong G•
May 16, 2018
So many unanswered questions in the forum. Peer reviews suck
교육 기관: Ponciano R•
Jan 10, 2019
The course is good, although it goes a little to fast.
교육 기관: Aneeshaa S C•
Jul 05, 2017
course should've had deeper python content.