Non CS stem phd new grad here wishing to break into data science machine learning as my first job out of xollege. Several guides suggest doing 1-2 side projects. I did the coursera ML online course last week, grew fasinated with CV after sitting in LeCun class yesterday and started making some toy app involving GAN today. Should i continue to finish the project to showcase to enployers, or is my time better spent on leetcode?
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If you want a job in ML, you are going to need to be able to talk about ML projects you have completed. It is even better if you can identify a way to use ML with some of your academic research data, thus directly showing the interviewer how your PhD expertise can be ported to a ML career. The level if leet code expertise required for the role varies by company, but most phone screens for an ML role will discuss previous ML work and ML competencies at least in part. There are bootcamps for stem PhDs that can help with this as well, for example I know several people who were successful transitioning to ML and data science using Insight.
Leetcode. Nobody gives fcuk even if you are Ian Goodfellow until you gonna write production code.
But how can someone show on resume that they’re good at leetcode? They can mention side projects on the resume though.
There will be at least couple of coding rounds no matter who you are. That is where leet code comes in handy