Do Hiring Managers Care about Udacity, Coursera, etc.?
May 21, 2020
431 Comments
I feel like seeing those drops credibility on someones resume really quick, but a lot of people put them on. They’re self paced learning material with no real grades/rigor/proof that you understand the material. Feels to me like if you had space on your resume left for them, then you don’t have enough experience. Mostly referring to the intro to ML targeted ones. I’m not bashing the people who take the courses. Self learning is great, but I just don’t really see how it demonstrates value or tangible skills.
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I dont reject someone for writing their coursers course but it does show a lack of awareness and devalus the rest of your cv
What really matters to me
0)If you have done a good 20% project at Google in a related topic preferably for 6+months.
1)PhD in a related field or any field.
2)Papers in related field
3)Non trivial Open source contribution in related field could just be qbout implementation aspects
4)Are you just a flat out great programmer/math olympiad winner. Someone who has contributed to c++ standards, linux kernel or ranked highly at topcoder/math olympiads.
Its not that I hate moocs but the barrier to entry is so small that its tough to evaluate and it looks bad on you for not having the judgement to realize the barrier to entry is small.
Don’t get me wrong, the courses/contests are good for you to learn and grow, and they are indicators of some amount of initiative (like lc count!) but ideally they shouldn’t be your major differentiators.
I would be lying if I said I didn’t benefit from having the Ivy League name on my resume, but if it’s pure learning you’re concerned about, some of these MOOCs are phenomenal, with much better production value than a university course. And I’m increasingly convinced that we will find alternative ways to “credential” people than the 4/5 yr university/academia system.
Practically, when hiring, I do take into account MOOCs, as long as there is evidence that the person actually completed the course.
Those courses are largely just an introduction to the topic, and while they can certainly give you a foundation that you could build upon if you wanted to pursue more advanced ML experience from there, the course alone does not provide anything substantial. Generally people come out of the course with a serviceable conversational knowledge about ML, and a rough idea of how to solve the already-solved problems in ML, but that’s about as far as it goes.
That may be good enough as a bonus for a general CS role which could be augmented by some ML approaches, but since I’m hiring for an ML-specific role creating novel ML approaches and solving state of the art problems, the fact that a coursera course was a learning experience for them means they’re not experienced enough for my team.
I assume you'd supplement the coursera with side projects, kaggle, etc. Anything particular?
A lot of Engineers preach that you don’t need masters/phd and just leetcode and study. But it’s evident here that there is still significant stigma of not having 4 year degree.