Linear Algebra Basics
- Offered byCoursera
Linear Algebra Basics at Coursera Overview
Duration | 21 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Linear Algebra Basics at Coursera Highlights
- Earn a Certificate upon completion
Linear Algebra Basics at Coursera Course details
- In this course, you will learn about the mathematical concepts related to linear algebra, which include vector spaces, subspaces, linear span, basis, and dimension
- It also covers linear transformation, rank and nullity of a linear transformation, eigenvalues, eigenvectors, and diagonalization of matrices
- The concepts of singular value decomposition, inner product space, and norm of vectors and matrices further enrich the course contents
Linear Algebra Basics at Coursera Curriculum
Getting Started with the Course
Course Overview
Vector Space
Binary Operations
Vector Space - I
Vector Space - II
Vector Subspace
Linearly Dependence and Independence of Vectors
Linear Combination and Linear Span of Vectors
Essential Reading: Real Vector Space
Recommended Reading: Real Vector Space
Practice Quiz: Week 1
Graded Quiz: Week 1
Linear Transformations and Eigenvalues
Basis and Dimension of a Vector Space
Linear Transformations
Null Space of a Linear Transformation
Range Space of a Linear Transformation
Matrix Associated with a Linear Transformation
Eigenvalues of a Matrix
Essential Reading: Basis and Dimension of a Vector Space
Essential Reading: Linear Transformations
Recommended Reading: Linear Transformations
Essential Reading: Eigenvalues of a Matrix
Live Session 1
Practice Quiz: Week 2
Graded Quiz: Week 2
Diagonalizable Matrices and Their Applications
Eigenvector of a Matrix
Special Matrices and Their Properties
Similar Matrices
Diagonalizable Matrices - I
Diagonalizable Matrices - II
Applications of Diagonalization of a Matrix
Essential Reading: Diagonalizable Matrices
Recommended Reading: Diagonalizable Matrices
Live Session 2
Practice Quiz: Week 3
Graded Quiz: Week 3
Singular Value Decomposition of a Matrix and Inner Product of Vectors
Spectral Decomposition
Singular Value Decomposition - I
Singular Value Decomposition - II
Applications of Singular Value Decomposition
Inner Product Space
Vector and Matrix Norms
Essential Reading: Spectral Decomposition and Singular Value Decomposition
Recommended Reading: Spectral Decomposition and Singular Value Decomposition
Essential Reading: Inner Product and Vector Norms
Live Session 3
Practice Quiz: Week 4
Graded Quiz: Week 4
Term-End Assignment
How to Attempt and Submit the Assignment
Introduction to Python for Linear Algebra
How to Use Coursera Jupyter Lab
Other courses offered by Coursera
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