More examples and code examples needed

The course needs a final assignment!

el contenido no se traduce muy bien

Not enough depth and using only csv

The final exam has broken questions

exercises could have been better.

I felt it was too fast to grasp.

Final assignment is quite messy

could not access the labs.

Not clear on the last part

This course is very tough

Lots of technical issues

Exams should be harder

la lala la la laa aaa

Not easy to follow.

Videos en Español

Muy poco practico

très bon cours

Very Math!

GOOD

good

Definitely not one of my favorite courses in the Data Science Certificate series. There were times I was ready to give up the pursuit of the certificate altogether during this class... There should have been a prerequisite for this course of the statistical tools and methods that would be covered in here... Sure I could program these things after this class, but i still dont understand why I would choose to use one over another? This is one of those classes where you walk away feeling more confused than when you went in... Also there were a lot of mistakes, typos, and obsolete things in the labwork - some reported and acknowledged months ago, but still not fixed in the lab (video I can understand, but not the labs)

The content is good, but if you are not familiar with Python, I wouldn´t recommend this course. There are a lot of typos in the video. The code contains a lot of errors where you have to find a solution. So, you are forced to debug their code often.

But if you are only interested in the course certificate, you could quickly go through the videos and quizzes, without any problems. It's easy to pass because the questions are like: What is the result of print("Hello world"). So no real challenges at all.

Please, try to fix the typos. Sometimes it was very embarrassing. Example (Week 3) instead of

"from sklearn.metrics ..." the video comes up with "from sklearn.metrixs ..."

This course will throw a lot of information at you despite how short the instructional videos are. I found myself referring to the various Python library documentation sites just to get a better understanding of the formulas and concepts being introduced.

The lab modules leave a lot to be desired as well. Most of the time, you are just clicking through until you get to the bottom of the notebook. Also, please be warned that some of the functions taught in this class will not work as they have been updated in the last few years.

I am disappointed this class was a struggle to get through and I hope future students have a better experience.

Seems more adequate for people who have a background in statistical analysis. The labs are confusing and there is no orientation to the tool being used so it has taken me quite a while to figure out how to even proceed through a lab. After spending considerable time doing the lab, it may not submit the results and Coursera assumes you haven't take it yet which means you have to do it all over again. Other courses I've taken are structured much more clearly, step-by-step, providing activities that allow you to gain confidence before throwing you off the deep end. This one could use the help of an instructional design expert.