I would say that my data science learning path was quite traditional. I did my bachelor's in economics and have a master's degree in global commerce and computer science (concentration in machine learning and artificial intelligence). I learned my skills from my business during my commerce degree and chose most technical elements from my master's in CS. I had a data science internship, and I was on my way.
Looking back, there was nothing wrong with my path, but knowing what I do now, what will I change about my learning journey? This question is particularly relevant for those who are new to the field. Many things have changed since I started, positions are more competitive and there are far more learning options. I hope that my experience can help others learn data science faster and more fully, and give them better job opportunities.
I will cite this article as saying that learning is slightly different for everyone. My word is not gospel, and there is a good chance that you will find something that works a little better for you. Nevertheless, I hope this is a good foundation from which to build. I hope this provides big picture priorities for you that are relevant when learning this field.
This article focuses more on where to learn (courses, bootcamps, degrees, etc.). I recommend these two articles for specific courses and online resources for field learning.
1) If I had to start learning data science again, how would I do it? (Santiago Vicz Segura)
2) My Self-Made Artificial Intelligence Masters Degree (Daniel Bourke)
For those who like the video version:
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