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Kursteilnehmer-Bewertung und -Feedback für Fundamentals of Quantitative Modeling von University of Pennsylvania

7,237 Bewertungen
1,431 Bewertungen

Über 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, you’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....


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.

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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1326 - 1350 von 1,404 Bewertungen für Fundamentals of Quantitative Modeling

von Johnny V

10. Juli 2016

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

von Michael S

6. Dez. 2017

Not enough about formulas or real world application. Was hoping to see examples applied in Excel.

von Sidney A

8. Mai 2016

Nice primer for modeling, but wish there were more workable problems to help hit the point home.

von Bharat J

20. Juni 2020

Too descriptive for a quantitative course. Would've preferred more problem solving exercises.

von Eike A H

9. Sep. 2019

-no explanation on errors

-too theoretical and abstract with lack of examples and own practice

von Siva S B

26. März 2018

Could have been more advanced from the perspective of practical use-cases of data modeling.

von jyoti v

23. Okt. 2018

The course is a bit too introductory for me. I'm looking for more challenging material.

von Kangkang W

17. Okt. 2016

most contents are explicit on ppt, it is sometimes not necessary to view the lectures.

von Josh R

17. Mai 2020

Lots of information, not much opportunity to apply practical usage to the theories

von martino g

30. März 2020

Content is good but the teacher is extremely boring. Had to struggle to finish it.

von Paul M

7. Juli 2020

My name was spelled incorrectly on my certificate, how to do I correct this?

von Mathew L

27. Apr. 2016

I would have liked the quizzes to explain why an answer was right or wrong.

von Brendan C

22. Mai 2018

good course, quizzes should not be locked though...disappointed with that.

von Deleted A

19. Feb. 2018

I think the contents of this course can be more difficult and challenging.

von Michelle l G

9. Feb. 2017

It was an interesting module, however, not sure how I will apply this in

von Gary V

11. Juli 2017

Very basic things that any person with a stats background should know

von Alec E

23. Juli 2020

Not that enjoyable. Decent information but pretty boring to watch.

von Abhed M

12. Jan. 2020

It should be more rigorous. I completed this course in three days.

von Dominique B

8. Apr. 2020

a bit too simple, I would have expected more practical excersises

von TheSovereignIndividual

13. Apr. 2020

Nice, course - could spend more time on practice and examples.

von Anup K D

2. Mai 2021

Need more examples. Logarithmic Regression was not very clear

von Olivia X

18. Sep. 2016

too easy. not enough practical skills or tools teaching

von Abhishek P

9. Feb. 2017

There should be lab or hands one calculation exercise.

von Steeve V

3. Feb. 2017

It was theoretical but provided an apt understanding.

von Roma

31. März 2018

Questions with actual raw data would be helpful.