It would be great to give student a list of exercises to practice before the quizzes. It will help understand the content (specially the calculations) better.

More exercises after each concept, and more specifically non-similar to the example exercises might be very helpful in cementing the concept

High-level review of different methodologies of modelling, however, course lacks deeper-level approach to actually implementing methods

The Explanation was a little too technical for me. Also I wasn't satisfied with the examples. Other than that, everything was solid.

I am sure content are quite good as lecture is knowledgeable but the background and material doesn't feel energetic and intuitive .

Really helpful in understanding the different models but if you wish to learn a bit more depth of modelling go to the next course.

Introduction to various topics is good but I would want to see many more examples where they are applied in real world scenarios

It could've gone deeper into the topic. Although it's called Fundamentals of quantitative modeling it don't got to be to basic.

This Course is very good for beginners who have absolutely no knowledge of Modelling. For Professionals, it is not of much use.

I was expecting the course to provide insight on how to use spread sheet and its respective formulae in mathematical modelling.

Well put together, however, if you have had a reasonable high school math education, most of the content will be known to you.

It would have been much more helpful to have practice opportunities besides the exam and exampled. I wanted to try it myself!

The instructor is good. Course material is very basic. However, it is not for someone having no knowledge of statistics.

As a guy from Machine Learning field, its models and concepts are so easy and simple for me, so it's lack of challenge.

More concrete exercises would have helped to anchor some principles. This was mostly a succession of videos and a quiz

This subject is totally numerical based, There should be more focus on numerical instead of theoretical knowledge.

I felt that there were insufficient examples to help us gain a better understanding of the concepts being taught

Many of the fundamentals are not explained. For example in Week 4 it is not explained how to calculate R2 or r

Assignments should be evaluated for all users (unpaid ones as well) like it is done for other Wharton courses.

Perhaps I was expecting too much given the reputation of the institution, but this is a course for beginners.

Could come a bit deeper in more complex examples at the end of the course. Most of them were too simple.

I think this course is too easy for students with Probability and Mathematical Statistics knowledges...

General description of the modeling, need further work or pre-understandings for some of the contents.

Felt a little rudimentary until the last week. I hope the specialization picks up after this point.