Johns Hopkins University - Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors
- Offered byCoursera
- Public/Government Institute
Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors at Coursera Overview
Duration | 14 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
- Overview
- Highlights
- Course Details
- Curriculum
Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors at Coursera Highlights
- Earn a certificate of completion
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- 18 quizzes
Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors at Coursera Course details
- This course is the second course in the Linear Algebra Specialization. In this course, we continue to develop the techniques and theory to study matrices as special linear transformations (functions) on vectors
- In particular, we develop techniques to manipulate matrices algebraically
- This will allow us to better analyze and solve systems of linear equations
- Furthermore, the definitions and theorems presented in the course allow use to identify the properties of an invertible matrix, identify relevant subspaces in R^n,
- We then focus on the geometry of the matrix transformation by studying the eigenvalues and eigenvectors of matrices
- These numbers are useful for both pure and applied concepts in mathematics, data science, machine learning, artificial intelligence, and dynamical systems
- We will see an application of Markov Chains and the Google PageRank Algorithm at the end of the course
Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors at Coursera Curriculum
Matrix Algebra
Matrix Operations
Inverse Matrices
Characterizations of Invertible Matrices
Matrix Operations
Inverse Matrices
Matrix Operations Practice
Inverse Matrices Practice
Matrix Algebra
Subspaces
Subspaces of R^n
Dimension and Rank
Introduction to Subspaces
Dimension and Rank
Subspaces Practice
Dimension and Rank Practice
Subspaces
Determinants
Introduction to Determinants
New Video
Cramer's Rule, Volume, and Linear Transformations
Introduction to Determinants
Properties of Determinants
Applications of Determinants
Introduction to Determinants Practice
Properties of Determinants Practice
Applications of Determinants Practice
Determinants
Eigenvectors and Eigenvalues
Introduction to Eigenvalues and Eigenvectors
The Characteristic Equation
Introduction to Eigenvalues and Eigenvectors
The Characteristic Equation
Introduction to Eigenvalues Practice
Characteristic Equation Practice
Eigenvectors and Eigenvalues
Diagonalization and Linear Transformations
Diagonalization
Eigenvectors and Linear Transformations
Diagonalization
Eigenvectors and Linear Transformations
Diagonalization Practice
Eigenvectors and Linear Transformations Practice
Diagonalization and Linear Transformations
Final Assessment
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