1. Wrap up
If you've made it this far, congratulations! In this video, we'll do a quick review of what we've learned so far.
2. Simulation concepts covered
In this course, we started off with an introduction to random variables and saw how we could use numpy random for generating random variables. We then saw how to use simulation for probability problems. Next we saw how to handle more complicated problems by modeling the data generating process. We took a slight detour to look at how simulation is used in resampling methods. Finally, we looked at more advanced applications including Monte Carlo integration.
3. Real-World applications designed
Along the way, you also designed and implemented a number of real world applications of simulation and, hopefully, had fun doing it! We ran an ecommerce ad simulation using a pretty involved data generating process. We used permutation testing to select the optimal design for a website to generate donations. In addition, we also built a robust simulation of a corn farm for business planning. Finally, we built a portfolio simulation to understand the tradeoffs between risk and reward.
4. Thank You & Good Luck!
I hope that these examples have given you an idea of how you can use simulation in your work. Simulation is a remarkably flexible and amazingly strong statistical tool that has been widely applied to domains like artificial intelligence, physics, computational biology and finance just to name a few. You now know how to apply this powerful tool. Please let us know what other novel applications and business problems you solve with simulation. Thank you and good luck!