Great!

amazing

Awesome

SUPERB

gooood

great

Great

The early videos in this course are well-done. I have studied this material before, and they provided a valuable "refresher" for me. The later videos attempt to cover too much ground, too quickly. The cross-disciplinary approach contributes to the feeling of confusion. I had also hoped that the data sets provided would be suitable for completing the course assignments. This was not the case, however. The OOL contains variables with many missing responses, and large numbers of response categories; the video examples are for categorical variables with two response categories The final week of the course frustrating, and I was unable to complete the assignment with the information provided.

This course is a great introduction to data management, SAS, and python. The videos and reading materials were very helpful and provided all the tools and strategies necessary to complete the assignments. The only reason I did not give the course a 5 start rating is due to the peer evaluation system. There was essentially no critical feedback provided throughout the course from peers. Most of the assignments I was asked to grade were spam or dead links. It was helpful to review the assignments of other students who submitted legitimate work, but these were very far and few between - maybe 4 out of the 15 assignments was asked to grade were submitted by real people.

There is a lot of self-teaching with these courses because there are no professors present to reach out to with questions. In addition, the course staff do not always respond promptly nor are they fully knowledgeable about all aspects of error messages that may arise out of coding. At times the code that were provided in the lecture videos were out of date and a lot of time was spent on googling to find the updated code. This is definitely not a beginner coder course and I do not recommend it to anyone who has not coded before.

This course is very simplistic, but interesting. I was able to complete the first 3 modules within a week, however I am somewhat skilled in this area. I was looking for something more difficult. However, my main goal was learning these techniques in python. It was frustrating that it took so long until we actually produced graphs (I don't like just looking at tables). However, all in all, it was useful and interesting -- I really like the applications-based approach. You get to analyze data about whatever YOU are interested in!

The course is great otherwise, however the certificate of this course just completed 'Data Management and Visualization' with no mention about the skills learnt or the grade attained.

Primary reason I enrolled to the course was to list 'SAS' (basic) as a skill in my resume, however the certificate does not mention anything about SAS. If at least the certificate said completed 'Data Management and Visualization with SAS', it would be a good value for money.

I strongly recommend Coursera should look into this. Thanks!

I'd pick 3.7 or so, really. The applied nature of the course is nice if you have a project in mind and to see the programming you learn in action. Without it, it might not be worth it because you could learn a lot of the SAS programming for free from SAS itself using their beginning programming coursework offered online (in fact potential students may consider taking the SAS programming essentials course before taking this because you learn a lot about the SAS coding framework that comes in handy for this class).

As an English speaking student, I felt this course was easy to follow and translated a complex subject into a step by step process of interpreting data. I like the hands-on development of a research question and learning the SAS and PYTHON Data Analytic software coding to extrapolate information from data sets. I didn't like the fact that it was difficult to get an instructor to respond in the forums and very difficult figuring out how to contact Coursera with any problems.

Simple and powerful Course. If you are a beginner. Just follow the instructions and Assignment Schedule. The course may seem a bit easy, if you are good at math and have some prior programming experience, yet you can be surprised with what new you learned by the end of the Course, considering the time you spend. Also you develop sound reasoning to answer your own questions regarding handling and presenting Data. The clarity you develop is worth it.

I really enjoyed this course. Have been using Python for years but never jumped into data management and visualization. This course helped me doing that and presenting results in a beautiful and useful way.

I am not rating with 5 starts because the rating system is cumbersome. I submitted my first assignment late and they were not peers to review my work so I am still waiting after a month of rejoining the course.

This course teaches about he basics of how to visualise, manage and manipulate data based on our hypothesis. It also entails different approaches to handle categorical and quantitative data. At the end it teaches how to interpret conclusions from the data. But I find it brief, little more description and practical examples and assignments could be better to hand good handson.

This is a good course to whom wants a macro introduction to Data Management along with some basics of Python programmation for data analysis. Python was actually for me the main learning.

The course is very practical with proposed use cases and you can also bring your own one.

If you are already working actively on data, you should find a more advance course.

It's a great course, but I would have preferred a bit more in-depth working with Python. Not all the coding examples and instructions apply to all the suggested datasets and one has to do a bit of extra research at times. But all in all, this course takes you through the most important steps of doing data analysis and visualization.

The course is well placed for beginners. Although I think there could be much more in the course as visualization also means plotting time series data and understanding the behavior of signals. If the course had more content and materials other than limited to histograms and bi-variate plots, I would have given 5 stars.

The content is easy to follow and is clearly explained without adding unnecessary complexity at this entry level. This specialization reaches its goals. Instead of trying to over achieve it keeps things simple.

I would recommend taking the "Data Science Specialization" as the next step.

The course requires to submit 4 assignments in which you can apply the basic skills learnt with SAS or Python. This is useful to effectively learn how to use these softwares. The course is clear and complete, although it provides with basic skills only

This course is very good especially for beginners getting started with SAS or python for data analytics. The lessons are very clear and easy to understand. Learnt a lot of valuable information and also enjoyed it.

Eine einfache Einführung in Data Management und Visualization.

ICh hätte mir einige weitere Details in Python bei der Erstellung von Grafiken gewünscht,

die ich stattdessen im Internet suchen musste.

It is a very nice course, although I was expecting something a little deeper / denser on both statistics and SAS programming. It is getting better on Module 2! =)