MATH 206 — Applied Calculus and Linear Algebra

Linear algebra in real coordinate space: eigenvalues and diagonalization, applications; orthogonality, Gram-Schmidt process, orthogonal projection; spectral theorem for symmetric matrices; singular value decomposition; positive definite matrices. Multivariable calculus: partial derivatives; linear and quadratic approximation; directional derivatives and gradient; classification of extreme values; constrained optimization. Examples and applications in data science.

• Credits: 3
• Faculty: Faculty of Science
• Department: Mathematics and Statistics
• Taught by: Kiwon Lee
• Prerequisites : MATH 133, and MATH 140 or MATH 139, and MATH 141.

Sections offered

• Section 001 (Lec), Tue Thu 11:35 am-12:55 pm — 70 seats open