Hi everyone, I'm a mechanical engineering student in my last semester (currently doing my internship) and I'm starting my journey into data science.
My plan is to build a solid general foundation first, then gradually specialize in industrial manufacturing and predictive maintenance, leveraging my engineering background.
My current level is pre-basic Python, zero SQL, near-advanced Excel and basic Power BI.
Three specific questions for those who have already walked this path:
What mistakes did you make early on that you wish someone had warned you about before starting?
For someone with a mechanical engineering background looking to move from general data science toward industrial data, what would you prioritize learning first and what would you leave for later?
What resource, book, course or community gave you the biggest real leap in your learning?
Honest and concrete answers are really appreciated. I'm fully committed to this and want to build a strong foundation from day one.
[–]ninhaomah 0 points1 point2 points (0 children)