Chevron Left
返回到 Fundamentals of Quantitative Modeling

學生對 宾夕法尼亚大学 提供的 Fundamentals of Quantitative Modeling 的評價和反饋

4.6
7,546 個評分
1,480 條評論

課程概述

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....

熱門審閱

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.

S
2020年11月30日

for the beginer like me i have experience in banking of 8 years still for me this fundamentals are new specially quantitative modelling.Kindly provide banking related examples in here too.\n\nthanks

篩選依據:

1376 - Fundamentals of Quantitative Modeling 的 1400 個評論(共 1,457 個)

創建者 Yuan Z

2019年3月9日

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

創建者 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.

創建者 Michael S

2017年12月6日

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

創建者 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.

創建者 Bharat J

2020年6月20日

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

創建者 Eike A H

2019年9月9日

-no explanation on errors

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

創建者 Siva S B

2018年3月26日

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

創建者 jyoti v

2018年10月23日

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

創建者 Kangkang W

2016年10月17日

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

創建者 Josh R

2020年5月17日

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

創建者 martino g

2020年3月30日

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

創建者 Paul M

2020年7月7日

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

創建者 Mathew L

2016年4月27日

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

創建者 Brendan C

2018年5月22日

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

創建者 Deleted A

2018年2月19日

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

創建者 Michelle l G

2017年2月9日

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

創建者 Gary V

2017年7月11日

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

創建者 Alec E

2020年7月23日

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

創建者 Abhed M

2020年1月12日

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

創建者 Chalal S

2021年10月8日

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

創建者 Dominique B

2020年4月8日

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

創建者 TheSovereignIndividual

2020年4月13日

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

創建者 Anup K D

2021年5月2日

Need more examples. Logarithmic Regression was not very clear

創建者 Olivia X

2016年9月18日

too easy. not enough practical skills or tools teaching

創建者 Abhishek P

2017年2月9日

There should be lab or hands one calculation exercise.