AI learning path
Learn the model, data, optimization, and evaluation foundations behind modern AI by training and inspecting small systems yourself.
For Developers, data practitioners, and technical beginners
6 resources
Microsoft
A project-based curriculum covering regression, classification, clustering, natural language processing, time series, and reinforcement learning with quizzes and assignments.
Microsoft
A broad curriculum spanning neural networks, computer vision, natural language processing, and other foundational AI techniques through lessons and labs.
PyTorch
An end-to-end quickstart through tensors, datasets, transforms, model construction, automatic differentiation, optimization, and saving a trained model.
TensorFlow
Official notebook tutorials for beginner workflows, data loading, Keras models, vision, text, structured data, and distributed training.
MIT 6.S191
A concise university course covering deep-learning foundations, sequence models, generative models, reinforcement learning, and current applications.
Harvard University · Brian Yu and David J. Malan
A project-led introduction to search, knowledge representation, uncertainty, optimization, machine learning, neural networks, and language in Python.
