ZurÃ¼ck zu Fundamentals of Quantitative Modeling

## Bewertung und Feedback des Lernenden fÃ¼r Fundamentals of Quantitative Modeling von University of Pennsylvania

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## Ãœber den Kurs

How can you put data to work for you? Specifically, how can numbers in a spreadsheet tell us about present and past business activities, and how can we use them to forecast the future? The answer is in building quantitative models, and this course is designed to help you understand the fundamentals of this critical, foundational, business skill. Through a series of short lectures, demonstrations, and assignments, youâ€™ll learn the key ideas and process of quantitative modeling so that you can begin to create your own models for your own business or enterprise. By the end of this course, you will have seen a variety of practical commonly used quantitative models as well as the building blocks that will allow you to start structuring your own models. These building blocks will be put to use in the other courses in this Specialization....

## Top-Bewertungen

AP

15. Juni 2019

Very clear and articulate explanation of the concepts. He doesn't skip a step in the sequencing ideas, drawing comparisons and differences, and illustrating both visually and story-telling. Excellent.

NC

30. Juli 2019

Very nice course for beginner, the mathematic level is not high (around french baccalaureat) so available to everyone. I enjoyed a lot this course that show how simple math can be used in real life.

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## 1426 - 1450 von 1,573 Bewertungen fÃ¼r Fundamentals of Quantitative Modeling

von mahee r

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27. Aug. 2017

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von Yangzhi G

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24. Juli 2017

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von John C

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30. Apr. 2018

I liked Professor Waterman; he is clear, gives examples, and doesn't just drone over the slides like my statistics professor did in college. However, the course itself felt a little too simplified. For example, when I arrived at the topic of multiple regression, concepts like collinearity and omitted variable bias, which are crucial to understand the fitness of your model, were not mentioned. This was a bit concerning because most business operations, I would assume, have multiple variables in play and would seem more practical to have a more in-depth focus on models reflecting that characteristic.

von Erik B

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2. Juni 2016

The materials in this course were great, but some of the math was not properly explained enough for the individuals to be able to see how the formulas were derived - especially some of the basic calculus and the regression materials. I believe it would have only added 5-10 more minutes in one or two modules to do so since there were so few examples given (This could be covered in subsequent courses within the specialization - I am not sure yet as I will be taking course #2 in the specialization starting next week). Otherwise, this course was a great overview of the types of models used.

von Ken O

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20. Dez. 2017

Content

This is essentially a statistics course couched in business terms, with a smattering of finance. The term quantitative modelling' is just how 'stats' has been 'rebranded' in the modern era. That is not a criticism from my point of view, but worth mentioning.

Difficulty level

Ultra-challenging for non-mathematician 'analysts'. The material is also structured sub-optimally. More cohesion would aid understanding. But the course is often rivetting and informative in ways that other groundings in stats fail to be, in my experience.

Conclusion

Difficult, but well worth the effort.

von richard l

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2. Dez. 2022

The concepts were concise and comprehensive. As someone with a Math degree I personally felt all the quizzes were easy. The course would probably be a good review for those who would like to be re-introduced to the topics again and encourage further reading. However, I felt that if I was someone that did not know these concepts prior to this course, I would probably be totally lost. The explanations were not in-depth enough and I felt like they needed more calculations and examples.

von Jose G

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21. Aug. 2017

The content as dry as it is was well presented. No problems there just be sure to have a good night sleep lest you find nodding in the middle of a module.

The reason for the three starts is a knock on Coursera for not letting me submit my last quiz on the last day of my paid subscription. I finished the content at 10:00 CST but I was not allowed to submit my last quiz. I had to pay for the next course in the certificate to get the completion certificate.

von Kunal S

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20. Juni 2020

The course was a good exposure to the theoretical concepts of Fundamentals of the Quanititative modelling. However, I would have found it more useful if the course had more practical applications that the I could work on myself. to help me understand the applications of the theoretical concepts better. Also, would have preferred the course to take through at least the basic of modelling these important models using some trial data set.

von Joshua G

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26. Mai 2020

Much of this course requires some previous knowledge of calculus and economic thinking. I found that much of this course was a mixture between my business calculus course and intermediate micro economics course that I have taken at college. I think it is unreasonable to call this a beginner level course given that I recognize a lot of the information from intermediate college level coursework.

von Erin K

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12. Dez. 2022

If you expect to learn about "financial modeling", it is highly different from your expectation.

It is not related to modeling things, which is needed for IBD.

But, if you are very interested in quantitative things, and if you want to work on the buy side for portfolio management things, it may help you(about 5%).

The level of all lectures is similar to the CFA Lv.1 's quant part.

von Jordan R

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9. MÃ¤rz 2016

A good introductory course but it would have been nice to see a bit more of the math behind the models. I don't think the assessments were worth upgrading to the paid version of the course though. They were basically memorization and regurgitation directly from the lecture videos with very little, if any, thinking required. A bit disappointing from an institution like Wharton.

von YUTING W

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3. Apr. 2016

The lecture is clear, but it's a fundamental lesson which could not learn many things, just theories. Furthermore, I suggest that there should be solution hints for Quiz, because students will be frustrated by not knowing the answers and not knowing how to fix them. In addition, the discussion broad is a little bit cold and lack of mentors to help students.

von Rechal S

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27. Mai 2020

The theory part is good but it is not explained with how the equation or graph is created, only meaning is explained which makes the course less dynamic as at the end of the course one feel that the knowledge is incomplete and have to go back and reunderstand when I will understand the logic and how those equation or graph is developed.

von Roshni R

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27. Okt. 2017

The course was helpful to understand key statistical concepts but I hope it would have been worked on a little bit more to make it less boring. I do understand it's rather difficult to make quantitative courses interesting but this is just my feedback to the makers of the course so they can take it into account as and if they desire.

von Kaiquan M

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12. Feb. 2016

This course was a good refresher of mathematical and statistical concepts. I found the mathematical and statistical concepts applied to modelling interesting. I never knew that what I learned in high school in the past can actually be used to come up with models to solve business problems. Some videos were a bit long though.

von Hanwen

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26. Jan. 2020

I thought this course was going to talk more about quantitative investment model, there's going to be more finance knowledge, but it's totally mathematical models, and I had actually learnt these mathematical models in other courses. I don't think the name of the lecture and introduction perfactly matches the contentIs.

von Anna D

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27. Feb. 2017

This is a quick run-through different types of distributions. I found it useful as a recap of things I learned in high school (!) and there were some additional insights. However, I think this course might be hard if you never did any more advanced (high school) math.

von Chetan D

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24. Nov. 2019

Good Course but the lecturer misses a lot of details and assumes the target students understand most of the basic math such as logarithms. Without further researching those concepts, the equations are a bit difficult to understand and interpret in a practical way.

von Suraj V

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16. Okt. 2016

I believe this was a very good course for beginners. However, from Wharton, I would have expected more realistic examples. I would have also liked some hands-on assignments. But, otherwise.. Great, great course from a beginners point-of-view! Thank you so much!

von Thanos V

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4. Mai 2020

The performance of the teacher was excellent, he is very communicative and you could watch him teach for hours, the reading material though should be more helpful, more available sources for further reading and any book chapters or hall books would be ideal

von Jose H

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12. Nov. 2017

It would have been nice to have some of the back work for some of the numbers provided in the RMSE, or R squared numbers. To better understand how those were calculated... instead of just taking someone's word for it.

von Eric O

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6. Sep. 2021

There is a fairly good explanation, but the calculation method should be explained in detail how the numbers of the answers are calculated, and in the question form, there should be an answer to every question.

von Himanshu G

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15. Mai 2020

The course covers a variety of concepts regarding the quantitative modelling which is good, but the description is very shallow. It would have been even better had it described concepts in more detail.

von Abhishek J

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30. Mai 2020

I found this course a beginner level plus as it's one of the modules of Business and financial modelling I prefer to have some practical education in this module to how to use these in a spreadsheet.

von Daniyal A

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18. Aug. 2017

Very basic stuff, not sure if it really helped me learn new things, just a bunch of terminology. Very well explain, perhaps I didn't fit the target audience (then again I'm just a student right now).