23/02/23 15:13:21
@daily
From this kid who studied all undergraduate Physics in 2 years!
https://www.scotthyoung.com/blog/2023/02/21/diego-vera-mit-challenge-math-physics/
One of the things I found quite useful was to gather resources that spoon-fed me insight in the shortest/most compressed time possible. Although this seems obvious in hindsight, one of the things I found over and over again with the challenge was how I could spend several hours trying to learn something based off of one resource, then turn to a different resource and understand it within minutes. Spending time collecting compressed yet insightful resources, I think, can have a huge impact.
One of the things I found useful here was to get immediate practice once I knew just enough. I think this is one of the reasons project-based learning can be so powerful: you have a problem and research your way into it versus researching your way into it and then seeing what to apply. In this way, the relevance of the necessary ideas or techniques becomes apparent.
Project
Maybe a topic could be something like: will energy efficiency improvements exacerbate the housing crisis?
I see that in UCL, they use models to generate household archetypes.
Forecasting would be a type of modelling?
The reason I think this all fits is that it’s using data science really and then combining it with things like causality and inference to try and tackle real world problems and figure out what is the case. I think no matter what question it’s directed towards, you learn useful skills along the way.
I’ll learn more about the world also (hopefully) and stay in touch with the energy sector.