This course is not well moderated, the material is confusing, and the quizzes were not tested before uploading them onto Coursera. This specialization is definitely not on par with other specializations I have done.

BLUF: There are better uses for your money and time.

poor instructor (too strong of an accent, no skills in talking with a teleprompter or generally putting life into what he says), material could be strongly improved, problems with assignments but no help in the forums

With all due respect to the lecturer (its obvious that he is intelligent and an expert on the subject), I found this lesson not easy to participate because of inordinate learning curve and fast accent.

It's a terrible course. honestly. The Professor's English is very often undecipherable, assignments have incorrect options, and there's no help from anybody in charge. Would give 0 stars if possible.

Poor communication and engagement skills. The syllabus has so much potential to be interesting but the teacher wasn't engaging and left most of the important details unexplained.

You get stuck after week 2 in the assigment, because the software needed is not allowed in all coporate enviroments. Explanations are nt non-native english speaker friendly.

Course quizzes and assignments are based around an outdated Excel extension that does not work anymore.

Week 3 quizzes have wrong answers.

I would rate negative if I could.

HORRIBLE HORRIBLE QUALITY...Terrible really....... never would recommend it and just a mediocre class

Test questions for week 3 are incorrect and do not match video / reading. Had to go to YouTube to figure out most of it.

Course using XLMiner, not Python. Poor choice. I used Python to get the results, all marked wrong!

Very poor course and delivery of subject matter was terrible - Do Not Take This Course!

Use of some other software can make this course better. xlminer has got a lot of bugs

This course is hard to follow for a non-naive English speaker.

Cannot understand the diction..

poor quiz design

This class provides a solid foundation on predictive modeling and analytics. It goes from basic models like linear regression to more complex models including neural networks and ensemble models. The material is covered using a tool named Analytic Solver which provides a different approach to the subject by focusing on the high level aspects of the models as opposed to doing the models in Python which would require the ability of the user to code and knowing how to use the many libraries out there for data science and machine learning. This allows the learner to cover a lot of techniques in relatively short period of time while at the same time providing the learner with a broad vision and understanding of the field of study.

Good course for introductory knowledge about predictive modeling (linear regression, classification, trees, neural network, etc). The accent of the professor makes it a bit hard to follow, nevertheless the content and follow-up exercises as well as quiz assignments and case studies are of superb quality. Highly recommend for those interested in business predictive methods.

Me gustaria que algunos videos (los mas importantes) se explayen mas en la explicacion de los resultados para poder conocer en profundidad que significan cada uno de ellos y así poder interpretarlos. Por ej. que significa un r2 de 0,54 o que significa un RMSE de cierto nivel.

Very rich and concise content, instructor very intelligent and objective, short and digestible videos. My only suggestion is to improve the quality of the neural network content, in my opinion, the very one too shallow compared with the rest of the excellent content.

Nice course, maybe you can update the instructions, the program has changed a little bit, is not difficult to change some parameters but it would be better with this video updates in XLminer activities. Thanks U Colorado Boulder and professor Dan Zhang

The course was really good and informative. A lot more ways to analysing data than one would normally come across and a good explanation of the various concept.

One suggestion would be sorting out the XLminer subscription of excel versions above 2016.

I rate this course as 5 stars as I found the information very useful. My only one issue was with XLminer. I think going over how to get it would be great (whether written somewhere on the course page or said in a short extra class).

Very challenging but very Informative course. I think this course is good stepping stone for anyone in interested in analytics career. Prof Dan Zhang also pointed to some books and websites which I found very helpful.

Good course to give a basic understanding of predictive modelling and analytics. Good assignments and opportunity to review peer submissions help reinforce the learnings.

This course talk about basic concept about preditive modeling and idea which you need to concern on. And the quizes are so great that you could practice what you learn.