Data Science is a multi-disciplinary evolving field. It has no well-defined route of education. A good data scientist should acquire decent software engineering skills, learn enough math and statistics to reason about data analysis and machine learning from first principles, and internalize enough knowledge about a domain to create realistic models. You don’t need to be exceptional in any of these areas, but you do need achieve basic fluency in all of them.
You can learn the first the necessary math / stats and computer science / software engineering from classes or self-study. The main value of a recognized university degree is that it’s the only credential recognized by many employers. If you don’t need the credentials, there are lots of free online resources you can use to teach yourself. Domain knowledge comes mostly from experience.
Remember that, there is a lot more to learn and know about Data Science, but whatever you learn, implement it by coding either in Python or R or Julia. That would be the key to become a successful Data Scientist.
