My first semester as PhD student is finally complete. It was a difficult semester for me and I had to develop a few skills in order to survive and keep sane. One skill was finding alternative ways to learn course content outside of the lecturers’ notes and recommended reading. It is difficult for professors to gauge everyone’s level so they standardize the material into a one-size-fits-all framework. That did not work for me in most cases, however, by looking online I discovered many intuitive lecture notes and examples that provided me with good exposure to topics.
Also, setting up time to do things that made me happy and active played a role. It is irrational to continue studying when you are unproductive and deprive yourself of breaks because that relaxation time is valuable in recharging your mental state and giving you a fresh set of eyes.
Lastly, simply having a good support network that you can count on can do so much. School is hard enough as it is so it is easy to succumb into negative habits or toxic people because sometimes you do not want to feel alone. I think this is good practice for everywhere in general, not just grad school. If I knew this from the beginning I felt that my transition to graduate school would have been much smoother.
Okay, enough ranting, I’ll discuss some of the interesting concepts that I learned over these past few months. My program stresses three fundamental topics: Probability Theory, Statistical Theory and Optimization. Our first year consists of taking the year long sequence on those three pillars. My favorite of them so far is probability theory, followed by statistics and then optimization. That determines the order in which I will discuss the topics.
I will break this blog post into 3 different sections, each providing a synopsis of what I got from the course. Of course, this wont be 100% percent accurate but I will try my best to be.