AI Engineering from Scratch
The article introduces an open-source AI engineering curriculum designed to teach algorithms from the ground up. It consists of 416 lessons across 20 phases, covering topics from linear algebra to autonomous swarms. The curriculum emphasizes understanding the underlying math before using frameworks like PyTorch.
- ▪The curriculum is maintained by Rohit Ghumare and is available for free on GitHub.
- ▪It includes lessons in four programming languages: Python, TypeScript, Rust, and Julia.
- ▪Each lesson follows a structured approach of reading the problem, deriving math, writing code, and running tests.
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FIG_000 · curriculum v1.0 · 2026 open source · MIT AI Engineeringfrom Scratch 416 lessons. 20 phases. Every algorithm built from raw math before a single framework gets imported. Maintained by Rohit Ghumare and contributors. Run on your own machine. FIG_006 · the stack memory · reasoning · kb Three repos compose into the agent stack the curriculum teaches. text { font-weight: 400; } .hbp-fill { fill: var(--blueprint); } .hbp-tint { fill: var(--blueprint-tint); } .hbp-tint-strong { fill: var(--blueprint-tint-strong); } .hink { fill: var(--ink); } .hink-mute { fill: var(--ink-mute); } .hmono { font-family: var(--font-mono); font-weight: 400; } .hserif { font-family: var(--font-body); font-weight: 400; } .hflow { stroke: var(--blueprint); stroke-width: 1.4; } REPO · REASONING agentbrain ★…
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