How to Learn AI from Scratch: A Step-by-Step Roadmap
Prerequisites for Learning AI
Contrary to popular belief, you don't need a PhD to learn AI. If you're starting from zero and want a structured, non-technical path, explore our best AI courses for beginners. However, a basic understanding of mathematics (algebra, statistics) and some programming experience will accelerate your progress.
Recommended: If you want a structured starting point with no coding required, see our best AI courses for beginners.
Step 1: Learn Python Basics
Python is the language of AI. Start with a beginner-friendly Python course that teaches fundamentals through practical projects. Andrew Ng's AI Python for Beginners is an excellent free option that teaches Python specifically in the context of AI applications.
Step 2: Math Foundations
Focus on linear algebra, calculus basics, probability, and statistics. You don't need to master every mathematical concept upfront - learn them as needed. Khan Academy offers free resources, and many AI courses include the math prerequisites you need.
Step 3: Machine Learning
Andrew Ng's Machine Learning course on Coursera is the gold standard starting point. It covers supervised and unsupervised learning, neural networks, and best practices. The updated version uses Python and modern tools, making it more practical than ever.
Step 4: Deep Learning and Beyond
Once you have ML fundamentals, dive into deep learning with the Deep Learning Specialization. From there, specialize based on your interests: computer vision, NLP, reinforcement learning, or generative AI. Build projects to solidify your knowledge and create a portfolio.