Course curriculum

  • 1

    Introduction to Linear Algebra

    • 10101 - Intro to Linear Algebra - Eng

    • 10102 - Linear Algebra Applications - Eng

    • 10103 - Linear Combination and Linear Equations - Eng

    • Quiz 1 - Linear Combination and Linear Equations

    • 10104 - System of Linear Equations - Eng

    • 10105 - Sol of Lin Sys - Elm Method - Eng

    • 10106 - Linear System Examples - Eng

    • Quiz 2 - System of Linear Equations

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  • 2

    Vectors

    • 10201 - What are Vectors - Eng

    • 10202 - Basic Operations on Vectors - Eng

    • Quiz 3 - Basic Operations on Vectors

    • 10203 - Interconversion between Polar and Rectangular Coordinates - Eng

    • Quiz 4 - Rectangular and Polar Coordinates

    • 10204 - Norm of a Vector - Eng

    • 10205 - Dot Product - Eng

    • Quiz 5 - Dot Product and Norm of a Vector

    • 10206 - Applications of Dot Product - Eng

    • 10208 - Span and Linear Independence - Eng

    • Quiz 6 - Linear Combination and Span of Vectors

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  • 3

    Matrices

    • 10301 - System of Linear Equations and Matrices - Eng

    • 10302 - Matrices Origin and Evolution - Eng

    • 10303 - Basic Operations and Properies - Eng

    • Quiz 7 - Basic Operations on Matrices

    • 10305 - Linear Transformation - Part 1 - Geometry and Intuition - Eng

    • 10306 - Linear Transformation - Part 2 - Common Transformations - Eng

    • 10307 - Linear Transformation - Part 3 - Math of Lin Trans - Eng

    • 10308 - Composition of Transformations - Eng

    • Quiz 8 - Matrix Multiplication and Linear Transformation

    • 10309 - Determinants - Eng

    • 10310 - Solution of Eqns - Cramer's Rule - Eng

    • Quiz 9 - Determinants

    • 10311 - Solution of Eqns - Matrix Inverse - Eng

    • Quiz 10 - Matrix Inverse

    • 10312 - Reduced Row Echelon Form - Eng

    • 10313 - Solution of Eqns - RREF - Eng

    • Quiz 11 - Reduced Row Echelon Form

    • 10316 - Eigenvalues and Eigenvectors - Eng

    • 10317 - Eigenvalues and Eigenvectors - 3 x 3 Systems - Eng

    • Quiz 12 - Eigenvalues and Eigenvectors

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  • 4

    Congratulations! You have successfully completed this course!

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