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The information in the course seems appropriate for an introductory level class and is presented clearly and in an understandable manner; the theoretical portion of the course is solid.

Having said that, the course could do with more exercises and practice tests in which you can apply and understand the formulas, how they are used, and why. The arithmetic component of the course felt glossed over and while that was not the focus of the course a few extra exercises could make things clearer and would not be a burden.

Fundamental knowledge of probability/statistics will help you better understand some of the concepts in the course, so if you have the time you could try checking those subjects before, or even while, studying this course.

Didactically, looking at the instructor's face for long periods of time gets tedious after a while, but this is just a minor issue.

There's a noticeable gap between the difficulty of the problems explored in the recorded lectures and some of the quiz questions. I was able to work through most of them because the majority of this course was a refresh of what I'd learned while earning my B.S. in Finance. That doesn't detract from the usefulness of the course--in fact I'd enrolled precisely because I wanted to sharpen that skill set. But I imagine this would be quite challenging for someone with absolutely no background in quantitative modeling already.

I'd give 5 stars if only we can see answers & explanations after finishing the quiz. I understand why answers aren't shown, probably because it's to prevent people from memorising answers before re-attempt the quiz to get pass. However, this can be circumvented by showing answers to people who have passed for the first time - and not record scores after that. I've been frustrating with not knowing where I got wrong. Although I can ask in Forum, it's hard for me to replicate what the selected/unselected choices are.

The content was very useful. The instructor is great and his presentations are very helpful. I rank this course with 4-stars because during the tests i couldn't see the explanations of my wrong answers. I have sent a ticket for an explanation but i haven't received an answer yet. Lastly, we haven't been tough how to transform back a log regression and i believe that you should add an extra presentation for math problems like this. Thank you for the knowledge, i am looking forward for the next course.

The course is informative and does its job of introducing the approach to modeling pretty nicely. It could be made more rigorous by going in-depth about probabilistic models, particularly the Monte Carlo simulations and the Markov models.

I would like to thank Prof. Richard Waterman and the Coursera team for making this course available. Prof. Waterman is precise and to the point. Those who find the video lectures to be slow paced (which includes me as well ) can watch it at 1.5-2X speed.

The instructor is very good at explaining a wide range of notions used in business modeling, statistics and probability theory. Would have liked to get a bit more in-depth insight into certain topics but this course is called "Fundamentals of Quantitative Modeling" and does very good what is supposed to do.

The reason I am not giving it a perfect score is because I felt like the assignments were too easy and the videos were a bit too long relative to the amount of information provided.