This course provides unified coverage of linear algebra and multivariable differential calculus. It discusses applications connecting the material to many quantitative fields. Linear algebra in large dimensions underlies the scientific, data-driven, and computational tasks of the 21st century. The linear algebra portion of the course includes orthogonality, linear independence, matrix algebra, and eigenvalues as well as ubiquitous applications: least squares, linear regression, Markov chains (relevant to population dynamics, molecular chemistry, and PageRank), singular value decomposition (essential in image compression, topic modeling, and data-intensive work in the natural sciences), and more. The multivariable calculus material includes unconstrained optimization via Graduateients and Hessians (used for energy minimization in physics and chemistry), constrained optimization (via Lagrange multipliers, crucial in economics), Graduateient descent, and the multivariable Chain Rule (which underlie many machine learning algorithms, such as backpropagation), and Newton's method (a crucial part of how GPS works).

前提条件: 国際的に認められたトレーニング機関からのオープンウォータースキューバ認定（および過去 1 年以内に 6 回の追加ログダイブ）以上、AAUS の健康診断に合格できること、およびインストラクターの同意。

創造における神のデザインと知恵は、宇宙の数学的配置と秩序から明らかです。

ダブル数学コースは、1年でAレベルの数学コースを修了し、2年目にさらに数学のAレベルを修了することで構成されます。