While I was studying the night before the CS188 final, I was lucky enough to experience one of those moments where everything just “clicks”. I understood how seemingly unrelated problems like inference, search, and RL fit together, and finally felt comfortable with the tricky, nitty-gritty “Select all that apply” problems that had tripped me up on the midterm. I ended up scoring more than 1.5 standard deviations above the mean on the final, and while I fell just short of an A overall, I left the class feeling that I had truly internalized what I’d learned, and ready to apply my learnings to research work and beyond.
CS188 has been immensely useful to me from an application standpoint — I’m currently doing research with RAISE Lab, studying RL for demand response in an energy-saving game framework, and my background from CS188 has been more than enough to help me understand interesting, novel papers I would’ve had no clue about otherwise. What’s been especially helpful is all the resources available for future reference, in between the projects, discussions, and electronic/written HWs. Any time I feel like I need a refresher on the intuition, or need a quick example of working Q-learning or particle filtering code, I know I can refer to my work from CS188.
Bottom line — I think CS188 is one of the most interesting, practically useful classes that I’ve taken at Cal, and it would be an honor to teach it. I’d love to help give other students the same intuition about AI concepts that I received from my TAs, and my ultimate dream would be to see the material “click” for them the same way it did for me.
uuid: [[202005031005 CS188 application]] date: May 3, 2020 tags: #applications