How I’d Learn Data Science If I Could Start Over (4 Years In)
A newer and more effective approach
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A New Perspective
Two years ago, I wrote a similar article explaining how I’d learn data science if I could start over. Now that I’m four years into my career, which is double the amount of time, I’ve realized that there is a much better approach to learning data science.
The problem with my previous guide is that it acts as a one-size-fits-all solution which simply isn’t the case. Because data science covers such a broad spectrum of skills and subjects, it’s only natural that particular skills matter a lot more for certain types of data scientists and a lot less for others.
And so, “How I’d Learn Data Science if I could start over” really starts with the question, “what aspects of data science am Interested in?” Is it statistical analysis? Is it deep learning? Is it building visualizations? Understanding this will help with prioritizing what skills to learn first. And if you’re unsure what aspects of data science you’re interested in, that’s completely okay because there are fundamental skills required by all types of data scientists that you can start with (as far I know).
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How I’d Re-Learn Data Science
Below is a simplified and generalized flowchart that I’d use to guide my learning if I had to learn data science all over again. I want to re-emphasize the simplicity of this flowchart in exchange for 100% completeness to make it as comprehensive as possible.
At a high level, the flowchart can be broken down into the following steps:
- Start with fundamental skills, SQL and Python.
- Decide whether your interest lies more in business-facing roles or research-facing roles.
- Based on what you chose in Step 2, select a specialized subject that interests you and that you…
