this post was submitted on 01 Aug 2023
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My undergrad was in Management Information Systems with a focus on Information Assurance. (So basically, Cybersecurity)
A general overview of network and systems architecture (particularly in an enterprise environment) was very helpful. Being given security projects and development projects in a simulated enterprise environment was also very helpful. These are things I definitely could've learned on my own, but finding projects to practice these skills on your own can be difficult, and finding an environment that simulates an enterprise environment to practice them in is even harder.
So then I worked in Cybersecurity at a fortune 50 company for a couple years and eventually worked on an analytics project and really enjoyed that. Then transitioned into analytics with the hope of picking up the skills necessary to transition into Cybersecurity Analytics eventually.
In Analytics, I worked on a few Data Science and Machine Learning projects. I REALLY enjoyed those. So I got a Professional Certification in Data Science and applied for my master's.
My Master's was in Data Science. This pushed me through practical projects that required me to learn more efficient ways to do the things I had been doing, more efficient ways to learn to products and tools, and to gain a deeper understanding of Statistics, Simulation, and Calculus.
I wouldn't say I got as many useful skills out of my Master's, but it got me used to working on large Data Science projects.