I've been researching data science, as a career path, and I'm finding a strange type of comfort in the structure of 'courses' as a knowledge base.
The Effective Tips course outlines the typical workflow of a Data Scientist, popular tools and software used (and that you need to learn), basic hard skills needed (that you need to learn), and tips on making LinkedIn and Github spiffy and niche specific. It further continues with tips for CV/Resume enhancements, Demo and Portfolio building, interviewing, cautions, advice, etc. So you're left having a game plan.
It doesn't really expand on everything in detail or train you in specifics. For instance, you need to know Python and/or R languages. Julia as a bonus. But you need to know Python AT LEAST. Still, the course won't teach you Python itself. You have to learn that another way. It outlines approximately a dozen critical tools, skills, and other things you need to be proficient in, at minimum.
The course bullet pointed the key soft skills that improve candidacy. So I took the course that goes into soft skills in more detail.
Something that fascinates me deeply is the art of collaborative communication. I've been trained (in life) to NOT think out loud— the exact opposite talent, lol. I realized that I'm bad at talking WHILE coding/working and describing what I'm doing while I'm doing it and I need a lot of practice at that. I tried to do that for awhile at my desk as I was doing some linear equations and my kids were looking at me like I was crazy— ha!
Anyhow, these are the cool certificates of completion Udemy issued after the courses.
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