Train, tune and distribute models with generative AI and machine learning capabilities
Link
Your CS degree, or other academic disciplines, may have taught you operating systems, data structures and algorithms, and stats; however, they probably didn’t teach you how to use the daily tools of the trade, let alone how to use them efficiently. This MIT winter lecture series and tutorials are aimed at those just entering the workforce. No longer will you need to keep a markdown file with git and ssh commands you copy paste in. This series includes critical topics on:
Even if this seems too rudimentary for you, it’s still worth a look -- there may be some things you wish you knew about today. If you do want something more advanced, check out this recent conversation on HackerNews about intermediate/advanced Python topics.
My Thoughts
I still remember my first day on the job… almost all these topics would have been useful. Instead, I was left to learn them myself or ask for a primer from senior co-workers. Today I find myself teaching these skills to the new hires. Coming armed with these skills to your first job might be underrated and hard to market, but they massively decrease the training time for junior data scientists. Knowing how to use them efficiently saves time and allows us to let computers automate the repetitive things. This also may save you from an embarrassing situation like data loss or an inability to execute. Arguably, this might be a good resource for fresh grad hires to have to complete as part of onboarding at your company.
Copy