5 Upskilling Traps to Avoid if You Really Want to Learn Data Science
Too often aspiring candidates and new professionals are making the same mistakes when trying to level up in data science.
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The number of hours I’ve spent learning data science is only slightly more than the amount of time I’ve thought about quitting data science.
While in school for my master’s in data science, I learned a hard truth about any technical discipline and especially data science: Learning in and of itself is a skill that takes years to master.
As a data engineer, one of my favorite parts of my job is the fact that, often, I’m getting paid to learn.
However, especially in school and at the beginning of my career, I found it difficult to consistently and effectively self-learn to the extent that I needed to in order to build proficiency and confidence in my technical skills.
After reexamining some of my earlier failed attempts to learn data skills, I’ve identified up skilling traps that I’ve fallen into and those I hope to help you avoid whether you’re beginning your career or trying to break into data science.
