C300

Mathematics for AI

This is not formula memorization. Students use code to recreate mathematical ideas and learn how vectors, distributions, gradients, and optimization become the engine of machine learning.

Math becomes visible when students can compute it.

C300 prepares students for machine learning by turning abstract concepts into experiments, graphs, and short implementations.

C301 Linear AlgebraVectors, matrices, transformations, high-dimensional data, similarity, embeddings, and representation.

C302 Probability & StatisticsData distributions, uncertainty, inference, metrics, sampling, hypothesis thinking, and statistical machine learning foundations.

C303 Calculus for AIDerivatives, gradients, loss functions, optimization, and how models learn by reducing error.

Upcoming C300 cohorts

Students can take each mathematics module independently, then combine them into a full AI math foundation when ready.

C301

Linear Algebra

Vectors, matrices, transformations, high-dimensional data, and representation.

Hours: 20 hours
Schedule: Monday 7:00-9:00 PM ET
Price: CAD $880

Join this cohort

C302

Probability & Statistics

Distributions, uncertainty, inference, evaluation metrics, and statistical thinking.

Hours: 20 hours
Schedule: Thursday 7:00-9:00 PM ET
Price: CAD $880

Join this cohort

C303

Calculus for AI

Derivatives, gradients, loss functions, optimization, and model learning.

Hours: 18 hours
Schedule: Sunday 10:00 AM-12:00 PM ET
Price: CAD $820

Join this cohort

Student outcomes

Students understand the math language behind modern AI and can connect formulas to working code.

Vector and matrix reasoning for data
Probability, statistics, uncertainty, and metrics
Gradient intuition and optimization
Mathematical confidence for C400 and C500