It's worthwhile to explain why many people find the OSDSM useful. The topics listed do indeed require depth to acquire an adequate proficiency to understand an

It's worthwhile to explain why many people find the OSDSM useful. The topics listed do indeed require depth to acquire an adequate proficiency to understand and command them. The OSDSM is most useful for people who don't know where to start, which is often the hardest part. The hardest things are often the most trivial in hindsight. Typical interaction: Q: I want to be a Data Scientist. What do you think I should study first? A: Build a basic proficiency in linear algebra, programming in python, and statistics. Then take cursory classes in the subjects in the OSDSM that interest you. You'll figure out what depth is most meaningful to you from there. Q: What does a Data Scientist actually need to know? A: Totally and completely depends on what you want to do. There are people who crunch click logs all day, people who comb the tendrils of search algorithms, and yet others who seek terrorists and criminals in statistical signs among the bits and bytes. See my last answer for relevant guidance. e.g. https://medium.com/@clarecorthell/the-brief-multi-tweet-enumeration-of-job-titles-encompassed-by-data-science-8d48a988e3a1 https://medium.com/@clarecorthell/the-brief-multi-tweet-enum...