I've seen this one in 'the old days', but never actually took it, just skimmed through the introduction. It was hard for me to grasp what I would take from it, even though it seemed interesting.

Can you please summarize what you took from the course? How would you use outside of the course the information you've learned? I would imagine something like "I've learned a model A that can be applied at real life situations such as a, b to get better insight", or maybe even "I can write a simulation to predict how some system will evolve in the future"?

I'm currently taking it and loving it. What I took from it so far is a toolbox for better thinking.

Examples:

  - why you only have to convince small % of people for your idea to be adopted by most people (schelling models)
  - how self-organization in cities and other domains works (lyapunov functions)
  - multiple models for decision making (decision trees, spatial choice models)
  - how economic growth works and how innovation is the only way to avoid economic stagnation (whether it's a good thing is another story)
  - how linear models are super useful to understand complex situations
  - how diseases spread and why R0 is so important (quite timely with covid!)
  - how to try different perspectives and heuristics to solve problems
  - how culture evolves and how innovation works to change the culture
  - how networks work
  - and more things!

That was one of the few MOOCs I completed back in the day. I don't really remember everything in the course--but not everything needs to be practical. One interesting thing I specifically do remember is Schelling's model which basically demonstrated that fairly subtle preferences can lead to very different outcomes.

easily one of the best courses around. teaches you a new way to look at problems. having learned about automata in cs, and see it applied to social sciences was mind blowing.