About this Course
최근 조회 43,917

Learner Career Outcomes

50%

이 강좌를 수료한 후 새로운 경력 시작하기

50%

이 강좌를 통해 확실한 경력상 이점 얻기

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

초급 단계

완료하는 데 약 15시간 필요

권장: 4 weeks of study, 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

Linear AlgebraEngineering Mathematics

Learner Career Outcomes

50%

이 강좌를 수료한 후 새로운 경력 시작하기

50%

이 강좌를 통해 확실한 경력상 이점 얻기

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

초급 단계

완료하는 데 약 15시간 필요

권장: 4 weeks of study, 4 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 5시간 필요

MATRICES

11개 동영상 (총 84분), 25 readings, 5 quizzes
11개의 동영상
Introduction1m
Definition of a Matrix | Lecture 17m
Addition and Multiplication of Matrices | Lecture 210m
Special Matrices | Lecture 39m
Transpose Matrix | Lecture 49m
Inner and Outer Products | Lecture 59m
Inverse Matrix | Lecture 612m
Orthogonal Matrices | Lecture 74m
Rotation Matrices | Lecture 88m
Permutation Matrices | Lecture 96m
25개의 읽기 자료
Welcome and Course Information1m
How to Write Math in the Discussions Using MathJax1m
Construct Some Matrices5m
Matrix Addition and Multiplication5m
AB=AC Does Not Imply B=C5m
Matrix Multiplication Does Not Commute5m
Associative Law for Matrix Multiplication10m
AB=0 When A and B Are Not zero10m
Product of Diagonal Matrices5m
Product of Triangular Matrices10m
Transpose of a Matrix Product10m
Any Square Matrix Can Be Written as the Sum of a Symmetric and Skew-Symmetric Matrix5m
Construction of a Square Symmetric Matrix5m
Example of a Symmetric Matrix10m
Sum of the Squares of the Elements of a Matrix10m
Inverses of Two-by-Two Matrices5m
Inverse of a Matrix Product10m
Inverse of the Transpose Matrix10m
Uniqueness of the Inverse10m
Product of Orthogonal Matrices5m
The Identity Matrix is Orthogonal5m
Inverse of the Rotation Matrix5m
Three-dimensional Rotation10m
Three-by-Three Permutation Matrices10m
Inverses of Three-by-Three Permutation Matrices10m
5개 연습문제
Diagnostic Quiz5m
Matrix Definitions10m
Transposes and Inverses10m
Orthogonal Matrices10m
Week One Assessment30m
2
완료하는 데 4시간 필요

SYSTEMS OF LINEAR EQUATIONS

7개 동영상 (총 71분), 6 readings, 3 quizzes
7개의 동영상
Gaussian Elimination | Lecture 1014m
Reduced Row Echelon Form | Lecture 118m
Computing Inverses | Lecture 1213m
Elementary Matrices | Lecture 1311m
LU Decomposition | Lecture 1410m
Solving (LU)x = b | Lecture 1511m
6개의 읽기 자료
Gaussian Elimination15m
Reduced Row Echelon Form15m
Computing Inverses15m
Elementary Matrices5m
LU Decomposition15m
Solving (LU)x = b10m
3개 연습문제
Gaussian Elimination20m
LU Decomposition15m
Week Two Assessment30m
3
완료하는 데 5시간 필요

VECTOR SPACES

13개 동영상 (총 140분), 14 readings, 5 quizzes
13개의 동영상
Vector Spaces | Lecture 167m
Linear Independence | Lecture 179m
Span, Basis and Dimension | Lecture 1810m
Gram-Schmidt Process | Lecture 1913m
Gram-Schmidt Process Example | Lecture 209m
Null Space | Lecture 2112m
Application of the Null Space | Lecture 2214m
Column Space | Lecture 239m
Row Space, Left Null Space and Rank | Lecture 2414m
Orthogonal Projections | Lecture 2511m
The Least-Squares Problem | Lecture 2610m
Solution of the Least-Squares Problem | Lecture 2715m
14개의 읽기 자료
Zero Vector5m
Examples of Vector Spaces5m
Linear Independence5m
Orthonormal basis5m
Gram-Schmidt Process5m
Gram-Schmidt on Three-by-One Matrices5m
Gram-Schmidt on Four-by-One Matrices10m
Null Space10m
Underdetermined System of Linear Equations10m
Column Space5m
Fundamental Matrix Subspaces10m
Orthogonal Projections5m
Setting Up the Least-Squares Problem5m
Line of Best Fit5m
5개 연습문제
Vector Space Definitions15m
Gram-Schmidt Process15m
Fundamental Subspaces15m
Orthogonal Projections15m
Week Three Assessment30m
4
완료하는 데 5시간 필요

EIGENVALUES AND EIGENVECTORS

13개 동영상 (총 120분), 20 readings, 4 quizzes
13개의 동영상
Two-by-Two and Three-by-Three Determinants | Lecture 288m
Laplace Expansion | Lecture 2913m
Leibniz Formula | Lecture 3011m
Properties of a Determinant | Lecture 3115m
The Eigenvalue Problem | Lecture 3212m
Finding Eigenvalues and Eigenvectors (1) | Lecture 3310m
Finding Eigenvalues and Eigenvectors (2) | Lecture 347m
Matrix Diagonalization | Lecture 359m
Matrix Diagonalization Example | Lecture 3615m
Powers of a Matrix | Lecture 375m
Powers of a Matrix Example | Lecture 386m
Concluding Remarks3m
20개의 읽기 자료
Determinant of the Identity Matrix5m
Row Interchange5m
Determinant of a Matrix Product10m
Compute Determinant Using the Laplace Expansion5m
Compute Determinant Using the Leibniz Formula5m
Determinant of a Matrix With Two Equal Rows5m
Determinant is a Linear Function of Any Row5m
Determinant Can Be Computed Using Row Reduction5m
Compute Determinant Using Gaussian Elimination5m
Characteristic Equation for a Three-by-Three Matrix10m
Eigenvalues and Eigenvectors of a Two-by-Two Matrix5m
Eigenvalues and Eigenvectors of a Three-by-Three Matrix10m
Complex Eigenvalues5m
Linearly Independent Eigenvectors5m
Invertibility of the Eigenvector Matrix5m
Diagonalize a Three-by-Three Matrix10m
Matrix Exponential5m
Powers of a Matrix10m
Please Rate this Course1m
Acknowledgments
4개 연습문제
Determinants15m
The Eigenvalue Problem15m
Matrix Diagonalization15m
Week Four Assessment30m
4.8
96개의 리뷰

Matrix Algebra for Engineers의 최상위 리뷰

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.

대학: CGMar 3rd 2019

Chasnov is outstanding! You will love the course but above all you will adore the way Chasnov marches on through the course and you are acquiring knowledge... He is a real instructor!

강사

강사의 이미지, Jeffrey R. Chasnov

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....

자주 묻는 질문

  • 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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