You’re an undergraduate. Either you’re graduating soon (like me) or you’re in the process of getting your first college degree. The process is not easy and I can only assume how difficult the pressures on Masters and Ph.D. students are. However, I have no clue about this, so it will not be my topic of focus. You could easily make the argument that I’m writing this for myself — that would be partially true. I still want to send this message out regardless. Applying to jobs in the Machine Learning field is not easy. Anyone who tells you otherwise did not work half as hard as you are working right now.
Being Objective:
Getting an undergraduate degree in Mathematics, Statistics, Computer Science, or any technical field related to Data Science and Machine Learning is an excellent way to get your foot in the door. Typically, you’re expected to have some form of internship or research experience during your four years in college. Getting experience afterwards is just as great. But when I talk about being objective of yourself, it’s not necessarily about your experience.
I am a rising senior in my university. This means I have less than a year left to graduate with a BS in Statistics. I constantly look back to myself as a sophomore taking my first upper division Statistics class — Analysis of Variance. When my professor was discussing how to find the overall sample mean, I saw a double summation for the first time in my entire life. I almost had a panic attack. This was the equation:
#statistics #mathematics #machine-learning #computer-science #data-science #deep learning