Python seems useful for programming, automation, data processing and working with APIs, while Generative AI introduces things like large language models, prompt engineering and AI-based applications.

For someone starting from the basics, would it be better to learn core Python first and then move into data handling with Pandas and NumPy, followed by machine learning and Generative AI?

I’ve also noticed that many tutorials jump directly into using AI tools and APIs. That’s useful for getting started quickly, but I’m wondering whether learning the fundamentals first makes it easier to understand what these systems are actually doing.

For those who have learned Python and AI, what worked best for you: following a structured learning path, building small projects, or learning different topics as you need them?

I’d especially like to hear about beginner-friendly projects that helped connect Python, data analysis and Generative AI in a practical way.