PDFs could have had more information on the lessons.

It's very quick and quizzes do not prepare properly.

quizzes were poorly written but interesting content

Some Quiz questions were a little bit open ended

didnt learn much and the quizzes were terrible

some parts of the sessions are very confused

Very hard to plug in formulas on the quizes.

Students need more explanation and practice.

Content is good but not practical enough

too superficial in the discussed ideas

quiz design is extremely confusing

A bit too basic at the beginning.

Quiz questions were ambiguous.

Material is not deep enough.

Good course overall

Very tough quizzes

No implementation

Good introduction

Poor quize

better

The Wharton School and Penn by extension has taken such tremendous effort to put together a great on-line offering. Some of their finest professors have made some of their rigorous coursework easily accessible via this platform.

This course however is one of the weakest that I have experienced both on this platform and from The Wharton School. The material covered is indeed dry in nature but the lectures - uninspiring - make it more so. The quizzes, designed to test your retention and understanding of material covered are ambiguously worded and not at all helpful in developing skill level around modeling. In more than one case, students are asked to write formulas that can use input data to create an output that will help make a decision. Many correct formulas are not recognized as correct by an overly rigid set of data in the grading system. That creates confusion - not helpful in developing skills.

Words such as "simplify" and "logical" appear in quizzes. These words are subjective, so the "logic" of a student may be different from the "logic" of the professor. Again, creates confusion.

It could be that one of the objectives of the professor is to get the student to think differently about modeling so as not to be overly linear. If that is the case, that is a good objective. However, whatever the objectives are - they are not clear nor directly put.

If you have little experience with financial models you will likely find this course to be both confusing and frustrating. If you have had some exposure to financial models you may find this course to be even more confusing and frustrating.

Pros: -Learned some new Excel shortcuts and tricks

-What-if Analysis and Solver

-Random variables and Monte Carlo Sim

Cons: -The combination of boring lectures and next to no screen aids, as well as bare bones "slides" seemed like the course was setting students up for failure. Minimal effort toward the learning process, just lectures and working in Excel.

-Not a single "fill in the formula" quiz question was marked correct, even though I took the formulas directly from the Excel sheet (modified of course for the example cells in the questions). My only explanation for this was that maybe there is only one "correct" answer that can be input? So if I say C8*H3 and he says H3*C8 maybe it's wrong?

-The prof enjoys writing (and sometimes speaking) at a very high level. Complex wording and sentences that span 3 or 4 lines are difficult to decode. I found myself reading one of the quiz questions 5 times in a row trying to figure out what he was actually looking for. We understand, you have a PhD. State the question simply. True communication is the response you get. I felt he was trying to force people to decode his complicated writing instead of helping us to understand the concepts. Student understanding should be of greater concern than complex sentence structure.

Overall: I would only recommend this class if you really want to learn some new excel functions and need to know linear models and Monte Carlo simulations. Even then, I would exhaust other resources first.

Unfortunately, I have to say I was disappointed with this course. Especially right after doing the "Foundations to Quantitative Modeling", which held a high standard containing very thorough- and clear instructions. I felt that parts of this course were not explained thoroughly enough which made it feel very "jumpy" and abstract. -This was then later verified in the tests where the question/thought; "did he even go though this?" often arose. Furthermore, the excel sheet that can be opened by oneself, on the side of listening to the videos, or reading the lessons, sometimes didn't fully match the one you saw in the video lesson. -For example; the reference points could be different.

Now I'm hoping the next course is more like the first one, which I very much enjoyed!

Contents of this part of the Specialization looked very promising (especially after a brilliant first part) but in reality this Introduction is shallow, rather monotonous, and I always had a feeling that it's like a patchwork and not something integral. The best part is that it doesn't take too long to complete, and the bulk of the time you spend decyphering the meaning of the questions in quizes (and at least some commentaries in answers would be great because this is not an exact science like math and there are a lot of possibilities for interpretations) . All in all, there are a lot of much more useful courses on Excel for models. I hope that other parts of the specialization will be closer to the 1st one.

Some of the ideas discussed are useful & new to me like linear programming and what-if analysis. The content is more suited to this specialization context instead of teaching excel in general so in case you are looking to learn excel, this is not a great course. I didn't like the quizzes, most of the questions added no value. My suggestion to the instructors would be less questions on the quizzes and more relevant to what you teach. I wouldn't complete the course if it wasn't a part of the specialization that I am attending.