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Avis et commentaires pour d'étudiants pour Model Thinking par Université du Michigan

2,047 évaluations
460 avis

À propos du cours

We live in a complex world with diverse people, firms, and governments whose behaviors aggregate to produce novel, unexpected phenomena. We see political uprisings, market crashes, and a never ending array of social trends. How do we make sense of it? Models. Evidence shows that people who think with models consistently outperform those who don't. And, moreover people who think with lots of models outperform people who use only one. Why do models make us better thinkers? Models help us to better organize information - to make sense of that fire hose or hairball of data (choose your metaphor) available on the Internet. Models improve our abilities to make accurate forecasts. They help us make better decisions and adopt more effective strategies. They even can improve our ability to design institutions and procedures. In this class, I present a starter kit of models: I start with models of tipping points. I move on to cover models explain the wisdom of crowds, models that show why some countries are rich and some are poor, and models that help unpack the strategic decisions of firm and politicians. The models covered in this class provide a foundation for future social science classes, whether they be in economics, political science, business, or sociology. Mastering this material will give you a huge leg up in advanced courses. They also help you in life. Here's how the course will work. For each model, I present a short, easily digestible overview lecture. Then, I'll dig deeper. I'll go into the technical details of the model. Those technical lectures won't require calculus but be prepared for some algebra. For all the lectures, I'll offer some questions and we'll have quizzes and even a final exam. If you decide to do the deep dive, and take all the quizzes and the exam, you'll receive a Course Certificate. If you just decide to follow along for the introductory lectures to gain some exposure that's fine too. It's all free. And it's all here to help make you a better thinker!...

Meilleurs avis

24 févr. 2017

Great content and lectures, that possibly provides new dimensions to look/explain the situation in context, I guess I will comeback for references to continue with this journey in to 'Model Thinking'

6 avr. 2018

The course presents a multitude of models that enable us to analyze human and systems behavior and interactions. By making implicit assumptions explicit we can understand real world processes better.

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426 - 450 sur 453 Avis pour Model Thinking

par kelly d

27 nov. 2019

Hard, but worth it!

par Karel G

25 oct. 2016

Great introduction.

par Ton T N K

11 sept. 2020

That's great!

par ruyanan

2 mai 2021


par Marek L

23 sept. 2016

Very good!

par Mimis R

11 oct. 2019


par ರತೀಷ್ പ

14 janv. 2016


par zhangmutanxi

21 mars 2016


par Mahmudul H

27 juin 2018


par Luiz C d P W F

4 avr. 2017


par Adem A

6 sept. 2016


par Nick M W

7 mars 2016


par Jaafar A

14 sept. 2020

Overall a very good course in terms of covering a broad range of topics. Suitable as a foundation to go onto to do more specialized courses in various parts of modelling. Some of the mathematical and quantitative methods could be better explained with more structured processes and formulae. For the learner that isn't familiar with these methodologies, some specific background reading on how best to approach the math would have been very useful. Having said that, well done to the lecturer and the rest of the staff and course organizers who tried their best to cover what are some quite complicated concepts.

par Andrey B S

23 sept. 2020

A pesar de que la materia es bellísima y desafiante. Le curso es extremadamente demandante de tiempo. Las evaluaciones son un total de 12 y son muy difíciles. Creo que la evaluaciones tienen una curva de dificulta que no es equivalente a lo visto en clase, lo cual termina provocando frustración y deserción entre los estudiantes.

par Milady M

6 mars 2017

i would like to see some subtitles in Spanish, to help me understand much better the main idea ! but in generally is so good and helpful!

par Wuan L H

23 oct. 2016

It is interesting and mind opening during the beginning and the middle of the course. Learned some interesting principle.

par Jaroslav A

6 mars 2021

Interesting but so boring

par Yechen H

13 oct. 2020

As a person who has a fair amount of Computer Science Education especially in the Artificial Intelligence area, I DO NOT recommend this course to someone with a similar background as I do. This course introduces several common models which a typical engineering/science student will encounter in her/his first two years of college study. The professor basically touches every model without much deep insights into how they might be practically applied to everyday choices/decisions. If you really want to Learn some Models, I would recommend the "Machine Learning" course here by Andrew Ng!

par Eli M

14 mars 2016

There have been some undesirable references to equations, in terms of equating modeling to economic growth and investment. I was interested by the syllabus and its outline of theories and the means to use models to study social sciences and systems sciences. After week 1, though, it was not a very interesting course so I considered trying to simply survey most of the videos to gain some more information, not necessarily for any more insight from the Professor from the University of Michigan.

par barry f

18 août 2020

Interesting topic but poor lecture method. Abandoned the course because lecturer difficult to follow

par Maya R

25 janv. 2021

Mathematical ability and statistics are required for this course.

par Cole P

17 janv. 2022

I​ couldn't get through it, a little tour of wikipedia would be far more enlightening:

-​ The lecturer remarks that application to the real world (and model fertility) are a goal of the course, but spends almost no time talking about real world applications.

-​ A lot of the lectures are getting bogged down in simple math: why do I need to go through look-up table examples for cellular automata?

-​ Lots of mistakes in each lecture, quiz questions are fairly poorly structured (asking who invented a particular model doesn't actually reinforce understanding)

-​ Class structure doesn't seem very thought out. Each category of models has an intro video that gives an overview as-if I were in a 10th grade english class, with 10+ minutes wasted with an overview where we should just jump right in.

T​o be honest, I'm not even very certain the lecturer understands many of the models he's presenting very well.

par terrylknox

28 févr. 2021

The videos may be useful for some but are difficult for others to follow (attention, accessibility, and other issues). This, combined with the lack of reading materials available (none) make information - especially the maths component of the course - harder to understand and absorb, given the quick nature and short timeline of the course. Given that the quizzes contain some math problems, it would be more helpful to have reading materials and small exercises to prepare for those quizzes instead of redoing the quiz rendering the learning process poor.

par Deleted A

4 mai 2020

The teacher's use of crutch words like sort of, like, and you know was distracting. Count how many times he says sort of! It's ironic for a university professor. But this is the United States, the land of substandard education - where everyone is special and receives a medal for participation.

par Ryan K

14 févr. 2017


-Too dated - links to many of the materials are unavailable.

-Instructors knowledge of some the models he cover is questionable (regression)


-Covers a lot of materials