Overview: I’m a self-taught data scientist sharing practical insights. Focus on basic coding, build essential math and stats awareness, and learn constantly. Embrace trial and error to develop expertise.
My experience as a self-taught data scientist has shown that a structured yet flexible approach is key to sustained progress. Focusing on foundational concepts and solid programming skills allowed me to gradually tackle more advanced topics. I began by building small projects to practice and integrate my theoretical learning. These experiments, although filled with errors at times, provided crucial lessons that refined my problem-solving abilities. The continuous process of challenging myself and revisiting core principles has been essential in developing my competence in data science.
i totally agree, sometimes u gotta mess up to learn. my journey shows that trial n’ error beats strict rules. experimenting, even when u slip, builds confidence and real skills in datascience. stick to your path and keep adjusting!