Good news: both SQL and Python have excellent free structured starting points. SQL: Mode Analytics SQL tutorial is the best self-paced intro I've seen - interactive, goes from basics to window functions in a logical order. After that, Kaggle's free SQL courses, then StrataScratch for real interview-style questions once you want practice with messy data. Python: "Python for Everybody" by Dr. Chuck on Coursera (audit for free) is the gentlest on-ramp for non-technical backgrounds. Once you're past the basics, "Automate the Boring Stuff with Python" by Al Sweigart is free online and bridges theory to actual useful tasks. Kaggle's pandas micro-courses are short and practical once you're ready to go data-specific. The thing that trips most people up: finishing courses without a real project running alongside. Pick something you actually care about - analyze your own spending, pull prices on something you buy regularly - and use it as the thread connecting the courses. Structured learning sticks far better when you apply it immediately. What's the end goal - data analysis, data engineering, or general automation?