On the Recurse Center’s Zulip community, someone posted this request for advice recently:
I’m currently in the early stages of preparing my application to Ph.D. programs in machine learning. I have unrelated/tangentially-related research experience in economics and a more recent stint in computational biology that used standard ML algorithms. Additionally, my undergrad was in econ and math, so I’m a little light on CS and feel that it would take me at least a semester to get up to speed for research in the field. Currently, I anticipate having my rec letters come from my two former PIs and an old math professor. Is it plausible to jump straight to a Ph.D. in CS, or should I be looking to do an MS in CS first?
With their permission, I’m publicly sharing a version of the advice I gave them, which seems to be common knowledge among academics but less well known outside the bubble.