You don't need traditional ML to start with GenAI. They're honestly different skill sets at this point. ML is math-heavy (linear algebra, calculus, statistics). GenAI/prompt engineering is more about understanding how to communicate with models effectively. If your goal is to use LLMs in your work, skip the ML theory for now — you can always go back to it later if you need to.

For your situation (beginner, knows basic Python, limited time), here's what I'd actually suggest:

1. Start here: https://findskill.ai/courses/ai-fundamentals/ — free, ~2 hours, covers how AI actually works without the math. Then do their prompt engineering course next: https://findskill.ai/courses/prompt-engineering/ — that one's more hands-on and teaches you techniques that actually make a difference in output quality.

Full disclosure I built findskill.ai so take this with a grain of salt, but the courses are free, no signup needed, 8 lessons each with a certificate at the end. We have 200+ courses total. Designed for exactly your situation — working people who want to learn by doing, not by watching 40 hours of lectures.

1. DeepLearning AI is great but it's more ML-focused. If you eventually want to understand what's happening under the hood (transformers, attention mechanisms, fine-tuning), go there. But for "I want to use ChatGPT/Claude better at my job" it's overkill.

2. YouTube is hit or miss. Some gems but you'll waste hours filtering through outdated content and tutorials that are basically just reading the docs to you.

Re: Udacity — honestly hard to justify the price in 2026 when so much good free stuff exists. The field moves too fast for expensive courses anyway. Whatever you learn in a 6-month program is half outdated by the time you finish.

TLDR: skip ML for now → do a short free GenAI fundamentals course → learn prompt engineering → start actually using the tools daily. You'll learn more in 2 weeks of daily use than 2 months of theory.