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LINEAR ALGEBRA AND OPTIMIZATION

MATH 345
과목 설명

Introduction to linear algebra, differential calculus in several variables, and basic optimization theory with applications to data science and related topics. Vectors, analytic geometry, matrices, linear functions, linear independence, orthogonality, inverses, partial derivatives and gradients, Taylor approximation, gradient descent, Lagrange multipliers, clustering, regression, classification. Implementation in Python.

선수과목

MATH 222 and (COMPSCI 200 , COMPSCI 220 , COMPSCI 300 , COMPSCI 310 , COMPSCI 320 , or placement in COMPSCI 300 ). Not open to students with credit for MATH 320 , MATH 340 , MATH 341 , or MATH 375 .

충족 요건
학점

미보고

개설 시기

미보고

평점
3.12

과거 데이터 대비 변화 없음

수료율
88.24%

과거 데이터 대비 변화 없음

A 비율
35.29%

과거 데이터 대비 변화 없음

학급 규모
17

과거 데이터 대비 변화 없음

Cumulative Grade Distribution

강사 (2026 Summr)

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유사 과목

APPLIED LINEAR ALGEBRA

MATH 443

Review of matrix algebra. Simultaneous linear equations, linear dependence and rank, vector space, eigenvalues and eigenvectors, diagonalization, quadratic forms, inner product spaces, norms, canonical forms. Discussion of numerical aspects and applications in the sciences.

LINEAR ALGEBRA AND DIFFERENTIAL EQUATIONS

MATH 320

An introduction to linear algebra and differential equations with emphasis on the relationship between the theory of linear algebra and analytical and numerical techniques for solving differential equations. Linear algebra topics include linear systems, matrices and their algebra, vector spaces and linear transformations, eigenvalues and eigenvectors. Topics from differential equations include first order ODE, homogeneous and nonhomogeneous linear systems, and numerical methods.

ELEMENTARY MATRIX AND LINEAR ALGEBRA

MATH 340

An introduction to linear algebra. Topics include matrix algebra, linear systems of equations, vector spaces, sub-spaces, linear dependence, span, basis, rank of matrices, determinants, linear transformations, coordinate representations, kernel, range, eigenvalues and eigenvectors, diagonalization, inner products and orthogonal vectors, symmetric matrices. Covers linear algebra topics in greater depth and detail thanMATH 320. Formal techniques in mathematical argument [MATH 341] not covered.

LINEAR ALGEBRA

MATH 341

The theory of linear algebra with an introduction to proofs and proof writing. Topics include vector spaces, linear dependence, span, basis, linear transformations, kernel, image, inner products and inner product spaces, geometry, eigenvalues, eigenvectors, standard matrix factorizations. Other content includes basic set theory, logical operations, quantifiers, direct and indirect arguments, and induction. Differential equations [MATH 320] not covered.

LINEAR OPTIMIZATION

COMPSCI/ISYE/MATH/STAT 525

Introduces optimization problems whose constraints are expressed by linear inequalities. Develops geometric and algebraic insights into the structure of the problem, with an emphasis on formal proofs. Presents the theory behind the simplex method, the main algorithm used to solve linear optimization problems. Explores duality theory and theorems of the alternatives.