Chevron Left
Fundamentals of Quantitative Modeling に戻る

ペンシルベニア大学(University of Pennsylvania) による Fundamentals of Quantitative Modeling の受講者のレビューおよびフィードバック

4.6
8,048件の評価

コースについて

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....

人気のレビュー

AP

2019年6月15日

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

2019年7月30日

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.

フィルター:

Fundamentals of Quantitative Modeling: 1451 - 1475 / 1,537 レビュー

by Johnny V

2016年7月10日

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

by Michael S

2017年12月6日

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

by Sidney A

2016年5月8日

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

by Bharat J

2020年6月20日

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

by Eike A H

2019年9月9日

-no explanation on errors

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

by S B

2018年3月26日

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

by jyoti v

2018年10月23日

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

by Kangkang W

2016年10月17日

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

by Josh R

2020年5月17日

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

by martino g

2020年3月30日

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

by Paul M

2020年7月7日

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

by Mathew L

2016年4月27日

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

by Brendan C

2018年5月22日

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

by Deleted A

2018年2月19日

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

by Michelle l G

2017年2月9日

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

by Gary V

2017年7月11日

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

by Alec E

2020年7月23日

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

by Abhed M

2020年1月12日

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

by Chalal S

2021年10月8日

The explaining is good, but the concepts in the course are basic.

by Dominique B

2020年4月8日

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

by TheSovereignIndividual

2020年4月13日

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

by Anup K D

2021年5月2日

Need more examples. Logarithmic Regression was not very clear

by Olivia X

2016年9月18日

too easy. not enough practical skills or tools teaching

by Abhishek P

2017年2月9日

There should be lab or hands one calculation exercise.

by Steeve V

2017年2月3日

It was theoretical but provided an apt understanding.