How I’d Learn AI in 2025 (If I Could Start Over)

A comprehensive roadmap for learning AI in 2025, starting with foundational mathematics (linear algebra, calculus, probability) and Python programming. The guide covers essential data science libraries (NumPy, Pandas, Matplotlib), then progresses through machine learning concepts including supervised learning (regression, classification algorithms), unsupervised learning (clustering), and reinforcement learning. It explains neural networks, deep learning architectures, and modern generative AI including transformers and large language models. The content includes practical learning resources like Khan Academy, Free Code Camp, and specific YouTube channels for hands-on implementation.