Data science is a vast body of knowledge encompassing science, business, and engineering, and there's still a lot yet to explore, like the oceans in the age of discovery. Recently in a few events for entry-level folks, I have shared my thoughts on navigating it with this old-fashioned map that I made.
First of all, I encourage people to practice sailing around Sea of Probability and Statistics, while also learning how to extract value connecting it to the business side. Only then, drift to the Bay of Computer Science, practicing around programming, data wrangling, and MLOps to name a few.
Then, I recommend that the uninitiated seafarer only ventures into deeper and stormier waters when they have mastered calmer and shallower ones. There be dragons and rough waters! In particular, the area around Deep Learning Point is dangerous for beginners, despite how accessible it seems.
Lastly, other exciting seas such as Actuarial Science, Econometrics, Financial Quantitative Analysis, Biostatistics, Geographic Information Systems, and Operations Research are typically not seen as part of data science, but very skilled data sailors have learned the ropes in those waters. It's definitely worth exploring these areas should you care to work in finance, insurance, logistics, economics, biotech, agriculture, and many other industries or disciplines that connect to them.