Getting into AI and ML without a math background — where to actually start
by Ting Yee Ong·May 26, 2026
I'm a marketing manager. My last math class was Form 5. I now work with ML outputs daily and understand enough to ask the right questions. Here's how I got there without a maths degree.
The honest prerequisite: You need enough statistics to understand distributions, correlation, and basic hypothesis testing. This is learnable without calculus. Khan Academy Statistics and Probability is free and sufficient.
Recommended path for non-technical people:
1. "AI for Everyone" by Andrew Ng (Coursera, free to audit) — conceptual, no code, excellent for building vocabulary
2. Practical Deep Learning for Coders (fast.ai) — if you want to go deeper, this teaches top-down and doesn't require heavy math upfront
3. "The Alignment Problem" and "Prediction Machines" — books that give you business and strategic context for AI
What to avoid: Starting with heavy mathematical ML textbooks. They're not wrong, but they're not the right entry point for building practical understanding.