If you’re curious about AI but don’t have a technical background, start here:
AI for Everyone (Coursera, by Andrew Ng)
A non-technical introduction to AI, its applications, and how it impacts business and society.
Google AI Essentials
Covers the fundamentals of AI and how to apply it in everyday tasks.
Teachable Machines (Hands-On, Beginner Friendly)
A playful tool to train simple AI models (image, audio, poses) without writing code.
AI for Everyone (Google AI Education)
Bite-sized resources and interactive learning for all.
If you know basic Python and want to get hands-on with AI/ML, these are your next steps:
Google AI’s Machine Learning Crash Course
A free, practical course with TensorFlow exercises covering supervised learning, classification, and neural nets.
Neural Networks: Zero to Hero (Andrej Karpathy, YouTube)
Beginner-friendly, step-by-step journey to building neural networks from scratch.
Practical Deep Learning for Coders (fast.ai)
A hands-on course focusing on applying deep learning quickly to real problems (vision, text, tabular).
If you’re comfortable with linear algebra, calculus, and programming, and want to go deeper into AI research and engineering:
Intro to Deep Learning (MIT)
A rigorous introduction to deep learning concepts, architectures, and real-world applications.
AI: Principles and Techniques (Stanford)
Stanford’s classic AI course covering search, optimization, probabilistic reasoning, and planning.
Language Modelling from Scratch (Stanford)
Deep dive into modern natural language processing (NLP) techniques and LLM foundations.
Generative AI (Stanford)
Learn how generative models (GANs, diffusion, transformers) are built and applied in cutting-edge AI.