Quantitative Foundations
Algebra, functions, and the math comfort you need before Math for AI & ML — not the math itself
6 phases. 20 lessons. 20 labs. 1 capstone. Built for adults who haven't done real math in years, not high schoolers — variables as labeled boxes, negative numbers understood geometrically, functions and graphs, exponents and logarithms, unit-circle trigonometry, and rate of change, each motivated by a real AI-flavored question before any formal notation. Sits directly before this platform's Math for AI & ML course.
- Lessons: —
- Labs: —
- Projects: —
- Level: Beginner
Curriculum
- Numbers, Variables & Expressions — Variables as labeled boxes, order of operations, negative numbers as geometric rotation, solving equations by undoing steps.
- Functions & Graphs — Functions as predictable rules, reading and building graphs, slope as rise over run, when a straight line stops being enough.
- Exponents, Logarithms & Growth — Exponential growth as repeated multiplication, logarithms as the exact undo, growth/decay, an honest preview of softmax and log-loss.
- Trigonometry & Geometry Intuition — Distance via the Pythagorean theorem, the unit circle, cos θ as an honest preview of cosine similarity, geometry in high dimensions.
- Sequences, Series & Rate of Change — Arithmetic vs. geometric sequences, moving averages, average rate of change converging into instantaneous rate of change.
- Capstone — Translating a real growth scenario into notation by hand, solving it, and verifying the solution with working Python.
Skills You Will Learn
- Algebraic Reasoning
- Functions & Graphs
- Exponents & Logarithms
- Trigonometric Intuition
- Rate of Change
- Mathematical Translation
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