If you're starting from scratch and want to build a career in AI, focus on learning in a structured sequence rather than jumping directly into advanced AI tools.

A good AI roadmap starts with the fundamentals. Focus first on Python programming, data structures, basic mathematics (especially linear algebra, probability, and statistics), and problem-solving. Once you're comfortable with these, move on to machine learning concepts, work on small projects, and gradually explore deep learning, NLP, and computer vision.

Start with core math and Python before touching ML frameworks. Build small projects along the way to solidify each concept before moving forward.

The step-by-step path you outlined is spot on, and I would echo that jumping into tools before the basics only slows you down. Python and the math first, then small projects, is the way I finally made progress myself. One thing I learned is that patience with the fundamentals pays off, just like in phlebotomy where solid training opens doors, and I have found the phlebotomy job outlook to be a handy reference for stable career moves when helping friends weigh options outside tech. Stick with that foundation and you will be fine.