Prerequisites · Math Academy track
Math Track
Harper has finished Algebra 2. Math Academy carries her through the AI math prerequisites in parallel with the coding curriculum. 用 Math Academy 补齐 AI 所需数学基础。
Why a separate math track
The AI syllabus assumes linear algebra, probability/statistics, and multivariable calculus — none of which are in Algebra 2. Math Academy's mastery-based, spaced-repetition system is ideal for building these efficiently. Run it daily (≈30–45 min) alongside the lectures.
What the AI syllabus needs vs. where to get it
| AI topic needed | Math Academy course | When |
|---|
| Functions, sequences, pre-calc gaps | Precalculus (only the gaps after Algebra 2) | Jun 2026 |
| Vectors, matrices, eigenvalues/eigenvectors, decompositions | Linear Algebra | Jul–Sep 2026 |
| Derivatives, gradients, multivariable calculus | Calculus I → Multivariable Calculus | Aug–Nov 2026 |
| Probability, distributions, Bayes' rule, statistics | Probability & Statistics | Sep–Dec 2026 |
| Gradient descent, convex optimization, duality | Taught in our Module 1 lectures (built on the calculus above) | Oct 2026 |
Sequencing tip
Linear algebra and calculus are the highest-leverage. Prioritize Math Academy's Linear Algebra first (needed for PCA, neural nets), then derivatives (needed for gradient descent and backprop). Probability can run a little later. Adjust pace based on the mastery bars on Harper's
progress page.
Note for a 12-year-old
This is genuinely advanced math for the age. The plan front-loads just enough of each area to use it in AI — we are not aiming for a full university math degree. Lectures re-teach each concept in applied context, so Math Academy and the lectures reinforce each other.