Education or Experience? Both.

What the musings of an old mathematician teach to machine learning engineers

Ever since the inception of machine learning, several debates have remained unsettled. If you follow the discussions in the community, you have likely seen many takes on the following questions.

“Do you need formal education or hands-on experience?”

“Should you focus on theory or practice?”

“Specialize in one area or strive to be a generalist?”

The answers you might find typically lie on an extreme part of the spectrum. There are strong arguments on both sides.

On the one hand, formal education does not imply in-depth knowledge, especially not in specialized fields that are not part of a standard curriculum. Requiring a degree to work as a data scientist can mean gatekeeping, denying entry to many talented engineers.

On the other hand, hands-on experience without understanding how things work is just user-level knowledge. If you know how to drive a car, it doesn’t mean that you can fix it when the engine starts to smoke. In tech, we all strive to be pit stop mechanics in competitive environ…