Deep-Learning Foundations
Synthesis
Karpathy's Zero to Hero is a code-first learning sequence: begin with automatic differentiation and backpropagation, then build language models through multilayer perceptrons, activation and gradient diagnostics, normalization, WaveNet-like structure, Transformers, and tokenizers. Language modeling is the teaching vehicle, not a claim that it is the only useful deep-learning domain. [src]
Its pedagogical pattern is to reconstruct mechanisms before treating them as library abstractions. That makes failures inspectable: a learner can connect tokenization, gradients, model architecture, and training behavior rather than only tune a high-level API. The course itself assumes Python and introductory mathematics, and its syllabus is described as ongoing. [src]
Learning model
The durable lesson is not a fixed curriculum order; it is an explanation chain. Build a small working mechanism, inspect intermediate behavior, then increase abstraction while retaining enough observability to explain what the abstraction hides.