About this Course
최근 조회 31,358

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

초급 단계

완료하는 데 약 13시간 필요

권장: 4 weeks of study, 3-4 hours/week...

영어

자막: 영어

배울 내용

  • Check

    Matrices

  • Check

    Systems of Linear Equations

  • Check

    Vector Spaces

  • Check

    Eigenvalues and eigenvectors

귀하가 습득할 기술

Eigenvalues And EigenvectorsGaussian EliminationEngineering MathematicsMatricesLinear Algebra
Course을(를) 수강하는 학습자
  • Technical Solutions Engineers
  • Traders
  • Economists
  • Scientists
  • Financial Advisors

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

초급 단계

완료하는 데 약 13시간 필요

권장: 4 weeks of study, 3-4 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 7시간 필요

MATRICES

11개 동영상 (총 84분), 25 readings, 5 quizzes
11개의 동영상
Introduction1m
Definition of a Matrix7m
Addition and Multiplication of Matrices10m
Special Matrices9m
Transpose Matrix9m
Inner and Outer Products9m
Inverse Matrix12m
Orthogonal Matrices4m
Rotation Matrices8m
Permutation Matrices6m
25개의 읽기 자료
Welcome and Course Information5m
Get to Know Your Classmates10m
Practice: Construct Some Matrices10m
Practice: Matrix Addition and Multiplication1m
Practice: AB=AC Does Not Imply B=C10m
Practice: Matrix Multiplication Does Not Commute10m
Practice: Associative Law for Matrix Multiplication10m
Practice: AB=0 When A and B Are Not zero10m
Practice: Product of Diagonal Matrices10m
Practice: Product of Triangular Matrices10m
Practice: Transpose of a Matrix Product10m
Practice: Any Square Matrix Can Be Written as the Sum of a Symmetric and Skew-Symmetric Matrix10m
Practice: Construction of a Square Symmetric Matrix10m
Practice: Example of a Symmetric Matrix10m
Practice: Sum of the Squares of the Elements of a Matrix10m
Practice: Inverses of Two-by-Two Matrices10m
Practice: Inverse of a Matrix Product10m
Practice: Inverse of the Transpose Matrix10m
Practice: Uniqueness of the Inverse10m
Practice: Product of Orthogonal Matrices10m
Practice: The Identity Matrix is Orthogonal10m
Practice: Inverse of the Rotation Matrix10m
Practice: Three-dimensional Rotation10m
Practice: Three-by-Three Permutation Matrices10m
Practice: Inverses of Three-by-Three Permutation Matrices10m
5개 연습문제
Diagnostic Quiz10m
Matrix Definitions15m
Transposes and Inverses15m
Orthogonal Matrices15m
Week One50m
2
완료하는 데 4시간 필요

SYSTEMS OF LINEAR EQUATIONS

7개 동영상 (총 71분), 6 readings, 3 quizzes
7개의 동영상
Gaussian Elimination14m
Reduced Row Echelon Form8m
Computing Inverses13m
Elementary Matrices11m
LU Decomposition10m
Solving (LU)x = b11m
6개의 읽기 자료
Practice: Gaussian Elimination10m
Practice: Reduced Row Echelon Form10m
Practice: Computing Inverses10m
Practice: Elementary Matrices10m
Practice: LU Decomposition10m
Practice: Solving (LU)x = b10m
3개 연습문제
Gaussian Elimination25m
LU Decomposition30m
Week Two30m
3
완료하는 데 7시간 필요

VECTOR SPACES

13개 동영상 (총 140분), 14 readings, 5 quizzes
13개의 동영상
Vector Spaces7m
Linear Independence9m
Span, Basis and Dimension10m
Gram-Schmidt Process13m
Gram-Schmidt Process Example9m
Null Space12m
Application of the Null Space14m
Column Space9m
Row Space, Left Null Space and Rank14m
Orthogonal Projections11m
The Least-Squares Problem10m
Solution of the Least-Squares Problem15m
14개의 읽기 자료
Practice: Zero Vector10m
Practice: Examples of Vector Spaces10m
Practice: Linear Independence10m
Practice: Orthonormal basis10m
Practice: Gram-Schmidt Process10m
Practice: Gram-Schmidt on Three-by-One Matrices10m
Practice: Gram-Schmidt on Four-by-One Matrices10m
Practice: Null Space10m
Practice: Underdetermined System of Linear Equations10m
Practice: Column Space10m
Practice: Fundamental Matrix Subspaces10m
Practice: Orthogonal Projections10m
Practice: Setting Up the Least-Squares Problem10m
Practice: Line of Best Fit10m
5개 연습문제
Vector Space Definitions15m
Gram-Schmidt Process30m
Fundamental Subspaces30m
Orthogonal Projections30m
Week Three50m
4
완료하는 데 7시간 필요

EIGENVALUES AND EIGENVECTORS

13개 동영상 (총 120분), 20 readings, 4 quizzes
13개의 동영상
Two-by-Two and Three-by-Three Determinants8m
Laplace Expansion13m
Leibniz Formula11m
Properties of a Determinant15m
The Eigenvalue Problem12m
Finding Eigenvalues and Eigenvectors (1)10m
Finding Eigenvalues and Eigenvectors (2)7m
Matrix Diagonalization9m
Matrix Diagonalization Example15m
Powers of a Matrix5m
Powers of a Matrix Example6m
Concluding Remarks3m
20개의 읽기 자료
Practice: Determinant of the Identity Matrix10m
Practice: Row Interchange10m
Practice: Determinant of a Matrix Product10m
Practice: Compute Determinant Using the Laplace Expansion10m
Practice: Compute Determinant Using the Leibniz Formula10m
Practice: Determinant of a Matrix With Two Equal Rows10m
Practice: Determinant is a Linear Function of Any Row10m
Practice: Determinant Can Be Computed Using Row Reduction10m
Practice: Compute Determinant Using Gaussian Elimination10m
Practice: Characteristic Equation for a Three-by-Three Matrix10m
Practice: Eigenvalues and Eigenvectors of a Two-by-Two Matrix10m
Practice: Eigenvalues and Eigenvectors of a Three-by-Three Matrix10m
Practice: Complex Eigenvalues10m
Practice: Linearly Independent Eigenvectors10m
Practice: Invertibility of the Eigenvector Matrix10m
Practice: Diagonalize a Three-by-Three Matrix10m
Practice: Matrix Exponential10m
Practice: Powers of a Matrix10m
Please Rate this Course10m
Acknowledgments1m
4개 연습문제
Determinants15m
The Eigenvalue Problem20m
Matrix Diagonalization30m
Week Four50m
4.8
71개의 리뷰Chevron Right

67%

이 강좌를 수료한 후 새로운 경력 시작하기

67%

이 강좌를 통해 확실한 경력상 이점 얻기

Matrix Algebra for Engineers의 최상위 리뷰

대학: JMar 12th 2019

Es muy bueno el curso de verdad que lo recomiendo mucho para todos aquellos estudiantes que cursan Álgebra Lineal ya que tiene todas las herramientas necesarias para aprender esa materia

대학: RHNov 7th 2018

Very well-prepared and presented course on matrix/linear algebra operations, with emphasis on engineering considerations. Lecture notes with examples in PDF form are especially helpful.

강사

Avatar

Jeffrey R. Chasnov

Professor
Department of Mathematics

홍콩과학기술대학 정보

HKUST - A dynamic, international research university, in relentless pursuit of excellence, leading the advance of science and technology, and educating the new generation of front-runners for Asia and the world....

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  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 수료증을 구매하면 성적 평가 과제를 포함한 모든 강좌 자료에 접근할 수 있습니다. 강좌를 완료하면 전자 수료증이 성취도 페이지에 추가되며, 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 콘텐츠만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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