I am talking about grad school or industry R&D lab level research in AI/ML.<p>Apart from being a good programmer, what other fundamental topics should one be well versed in to become a good researcher in this domain?<p>I am in undergrad and I would love to apply to grad school after I finish. What topics should I study and from where? Books, courses, anything? I want to prepare ahead.
I see many people dive into ML research by tinkering along the way. Although I have no objection to particular tastes, two courses that made modern ML easy for me were:<p>1. Linear Dynamical Systems by Stephen Boyd [<a href="https://ee263.stanford.edu/archive/" rel="nofollow">https://ee263.stanford.edu/archive/</a>]<p>2. Convex Optimisation by Stephen Boyd. [<a href="https://see.stanford.edu/Course/EE364A" rel="nofollow">https://see.stanford.edu/Course/EE364A</a>]<p>Both lecture series and course notes are availabe from the official page of the instructor.