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Linear Algebra

4.0 (0)
16 learners

What you'll learn

This course includes

  • 35.5 hours of video
  • Certificate of completion
  • Access on mobile and TV

Course content

1 modules • 143 lessons • 35.5 hours of video

Linear Algebra

143 lessons • 35.3 hours
  • Introduction to the inverse of a function | Matrix transformations | Linear Algebra | Khan Academy18:54
  • 3 x 3 determinant | Matrix transformations | Linear Algebra | Khan Academy10:01
  • Exploring the solution set of Ax = b | Matrix transformations | Linear Algebra | Khan Academy16:34
  • Introduction to projections | Matrix transformations | Linear Algebra | Khan Academy14:37
  • Transpose of a matrix | Matrix transformations | Linear Algebra | Khan Academy08:37
  • Determinant when row multiplied by scalar | Matrix transformations | Linear Algebra | Khan Academy13:20
  • Linear transformations | Matrix transformations | Linear Algebra | Khan Academy13:52
  • Rule of Sarrus of determinants | Matrix transformations | Linear Algebra | Khan Academy07:18
  • Deriving a method for determining inverses | Matrix transformations | Linear Algebra | Khan Academy18:00
  • Preimage and kernel example | Matrix transformations | Linear Algebra | Khan Academy15:23
  • Proof: Invertibility implies a unique solution to f(x)=y | Linear Algebra | Khan Academy22:41
  • A more formal understanding of functions | Matrix transformations | Linear Algebra | Khan Academy16:01
  • Transposes of sums and inverses | Matrix transformations | Linear Algebra | Khan Academy08:40
  • Compositions of linear transformations 2 | Matrix transformations | Linear Algebra | Khan Academy16:31
  • Showing that A-transpose x A is invertible | Matrix transformations | Linear Algebra | Khan Academy12:34
  • Visualizations of left nullspace and rowspace | Linear Algebra | Khan Academy19:50
  • n x n determinant | Matrix transformations | Linear Algebra | Khan Academy18:40
  • Matrix product associativity | Matrix transformations | Linear Algebra | Khan Academy11:59
  • Expressing a projection on to a line as a matrix vector prod | Linear Algebra | Khan Academy16:41
  • Matrix condition for one-to-one trans | Matrix transformations | Linear Algebra | Khan Academy19:59
  • Image of a subset under a transformation | Matrix transformations | Linear Algebra | Khan Academy18:11
  • Linear transformations as matrix vector products | Linear Algebra | Khan Academy17:32
  • Relating invertibility to being onto and one-to-one | Linear Algebra | Khan Academy06:31
  • Simpler 4x4 determinant | Matrix transformations | Linear Algebra | Khan Academy09:13
  • Transpose of a matrix product | Matrix transformations | Linear Algebra | Khan Academy08:50
  • Upper triangular determinant | Matrix transformations | Linear Algebra | Khan Academy08:07
  • Determinant when row is added | Matrix transformations | Linear Algebra | Khan Academy16:55
  • (correction) scalar multiplication of row | Matrix transformations | Linear Algebra | Khan Academy02:52
  • Simplifying conditions for invertibility | Matrix transformations | Linear Algebra | Khan Academy06:37
  • More on matrix addition and scalar multiplication | Linear Algebra | Khan Academy10:42
  • Formula for 2x2 inverse | Matrix transformations | Linear Algebra | Khan Academy18:20
  • Determining whether a transformation is onto | Linear Algebra | Khan Academy25:51
  • Compositions of linear transformations 1 | Matrix transformations | Linear Algebra | Khan Academy12:21
  • Determinant as scaling factor | Matrix transformations | Linear Algebra | Khan Academy20:10
  • Vector transformations | Matrix transformations | Linear Algebra | Khan Academy14:19
  • Duplicate row determinant | Matrix transformations | Linear Algebra | Khan Academy08:19
  • Rotation in R3 around the x-axis | Matrix transformations | Linear Algebra | Khan Academy12:18
  • im(T): Image of a transformation | Matrix transformations | Linear Algebra | Khan Academy16:37
  • Determinant after row operations | Matrix transformations | Linear Algebra | Khan Academy10:25
  • Linear transformation examples: Rotations in R2 | Linear Algebra | Khan Academy17:52
  • Unit vectors | Matrix transformations | Linear Algebra | Khan Academy06:59
  • Transpose of a vector | Matrix transformations | Linear Algebra | Khan Academy12:06
  • Showing that inverses are linear | Matrix transformations | Linear Algebra | Khan Academy21:24
  • Determinant and area of a parallelogram | Matrix transformations | Linear Algebra | Khan Academy21:37
  • Determinants along other rows/cols | Matrix transformations | Linear Algebra | Khan Academy09:03
  • Distributive property of matrix products | Matrix transformations | Linear Algebra | Khan Academy09:52
  • Matrix vector products as linear transformations | Linear Algebra | Khan Academy17:04
  • Rowspace and left nullspace | Matrix transformations | Linear Algebra | Khan Academy23:19
  • Linear transformation examples: Scaling and reflections | Linear Algebra | Khan Academy15:13
  • Example of finding matrix inverse | Matrix transformations | Linear Algebra | Khan Academy06:22
  • rank(a) = rank(transpose of a) | Matrix transformations | Linear Algebra | Khan Academy11:14
  • Sums and scalar multiples of linear transformations | Linear Algebra | Khan Academy15:09
  • Determinant of transpose | Matrix transformations | Linear Algebra | Khan Academy14:10
  • Matrix product examples | Matrix transformations | Linear Algebra | Khan Academy18:14
  • Surjective (onto) and injective (one-to-one) functions | Linear Algebra | Khan Academy09:32
  • Preimage of a set | Matrix transformations | Linear Algebra | Khan Academy05:23
  • Matrices to solve a system of equations | Matrices | Precalculus | Khan Academy16:33
  • Matrices: Reduced row echelon form 3 | Vectors and spaces | Linear Algebra | Khan Academy12:08
  • Matrices: Reduced row echelon form 1 | Vectors and spaces | Linear Algebra | Khan Academy17:43
  • Classic video on inverting a 3x3 matrix part 1 | Matrices | Precalculus | Khan Academy16:45
  • Singular matrices | Matrices | Precalculus | Khan Academy14:27
  • Matrices to solve a vector combination problem | Matrices | Precalculus | Khan Academy14:20
  • Idea behind inverting a 2x2 matrix | Matrices | Precalculus | Khan Academy14:15
  • Matrices: Reduced row echelon form 2 | Vectors and spaces | Linear Algebra | Khan Academy07:37
  • Classic video on inverting a 3x3 matrix part 2 | Matrices | Precalculus | Khan Academy13:36
  • Vector triple product expansion (very optional) | Vectors and spaces | Linear Algebra | Khan Academy14:25
  • Normal vector from plane equation | Vectors and spaces | Linear Algebra | Khan Academy09:58
  • Point distance to plane | Vectors and spaces | Linear Algebra | Khan Academy12:12
  • Distance between planes | Vectors and spaces | Linear Algebra | Khan Academy14:45
  • Eigenvalues of a 3x3 matrix | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy14:08
  • Change of basis matrix | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy17:55
  • Finding eigenvectors and eigenspaces example | Linear Algebra | Khan Academy14:34
  • Eigenvectors and eigenspaces for a 3x3 matrix | Linear Algebra | Khan Academy15:34
  • Projections onto subspaces | Linear Algebra | Khan Academy17:26
  • Introduction to orthonormal bases | Linear Algebra | Khan Academy11:16
  • Least squares examples | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy18:50
  • Showing that an eigenbasis makes for good coordinate systems | Linear Algebra | Khan Academy13:09
  • Alternate basis transformation matrix example part 2 | Linear Algebra | Khan Academy12:36
  • Changing coordinate systems to help find a transformation matrix | Linear Algebra | Khan Academy29:00
  • Orthogonal complement of the nullspace | Linear Algebra | Khan Academy03:27
  • Representing vectors in rn using subspace members | Linear Algebra | Khan Academy27:00
  • Least squares approximation | Linear Algebra | Khan Academy15:32
  • Introduction to eigenvalues and eigenvectors | Linear Algebra | Khan Academy07:43
  • Transformation matrix with respect to a basis | Linear Algebra | Khan Academy18:02
  • Orthogonal complements | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy22:08
  • Subspace projection matrix example | Linear Algebra | Khan Academy13:04
  • Another least squares example | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy13:25
  • Finding projection onto subspace with orthonormal basis example | Linear Algebra | Khan Academy06:42
  • Coordinates with respect to orthonormal bases | Linear Algebra | Khan Academy15:28
  • Another example of a projection matrix | Linear Algebra | Khan Academy21:36
  • Gram-Schmidt example with 3 basis vectors | Linear Algebra | Khan Academy13:57
  • Projection is closest vector in subspace | Linear Algebra | Khan Academy09:05
  • A projection onto a subspace is a linear transformation | Linear Algebra | Khan Academy16:16
  • Unique rowspace solution to Ax = b | Linear Algebra | Khan Academy19:12
  • Example using orthogonal change-of-basis matrix to find transformation matrix | Khan Academy27:04
  • Alternate basis transformation matrix example | Linear Algebra | Khan Academy13:20
  • Invertible change of basis matrix | Linear Algebra | Khan Academy13:34
  • dim(v) + dim(orthogonal complement of v) = n | Linear Algebra | Khan Academy09:27
  • Example solving for the eigenvalues of a 2x2 matrix | Linear Algebra | Khan Academy05:39
  • Rowspace solution to Ax = b example | Linear Algebra | Khan Academy19:38
  • The Gram-Schmidt process | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy19:24
  • Proof of formula for determining eigenvalues | Linear Algebra | Khan Academy09:19
  • Gram-Schmidt process example | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy13:14
  • Visualizing a projection onto a plane | Linear Algebra | Khan Academy09:28
  • Coordinates with respect to a basis | Linear Algebra | Khan Academy16:08
  • Projections onto subspaces with orthonormal bases | Linear Algebra | Khan Academy16:14
  • Orthogonal matrices preserve angles and lengths | Linear Algebra | Khan Academy11:16
  • Orthogonal complement of the orthogonal complement | Linear Algebra | Khan Academy12:18
  • Defining the angle between vectors | Vectors and spaces | Linear Algebra | Khan Academy25:11
  • Proof: Relationship between cross product and sin of angle | Linear Algebra | Khan Academy18:09
  • Matrix vector products | Vectors and spaces | Linear Algebra | Khan Academy21:10
  • Span and linear independence example | Vectors and spaces | Linear Algebra | Khan Academy16:53
  • More on linear independence | Vectors and spaces | Linear Algebra | Khan Academy17:38
  • Showing relation between basis cols and pivot cols | Linear Algebra | Khan Academy08:33
  • Showing that the candidate basis does span C(A) | Vectors and spaces | Linear Algebra | Khan Academy13:40
  • Introduction to linear independence | Vectors and spaces | Linear Algebra | Khan Academy15:46
  • Visualizing a column space as a plane in R3 | Vectors and spaces | Linear Algebra | Khan Academy21:11
  • Dimension of the column space or rank | Vectors and spaces | Linear Algebra | Khan Academy12:48
  • Vector triangle inequality | Vectors and spaces | Linear Algebra | Khan Academy18:53
  • Linear combinations and span | Vectors and spaces | Linear Algebra | Khan Academy20:35
  • Defining a plane in R3 with a point and normal vector | Linear Algebra | Khan Academy13:53
  • Vector dot product and vector length | Vectors and spaces | Linear Algebra | Khan Academy09:10
  • Proof: Any subspace basis has same number of elements | Linear Algebra | Khan Academy21:35
  • Null space and column space basis | Vectors and spaces | Linear Algebra | Khan Academy25:13
  • Dimension of the null space or nullity | Vectors and spaces | Linear Algebra | Khan Academy13:59
  • Parametric representations of lines | Vectors and spaces | Linear Algebra | Khan Academy24:46
  • Introduction to the null space of a matrix | Vectors and spaces | Linear Algebra | Khan Academy10:23
  • Cross product introduction | Vectors and spaces | Linear Algebra | Khan Academy15:47
  • Linear subspaces | Vectors and spaces | Linear Algebra | Khan Academy23:29
  • Null space 2: Calculating the null space of a matrix | Linear Algebra | Khan Academy13:07
  • Proof of the Cauchy-Schwarz inequality | Vectors and spaces | Linear Algebra | Khan Academy16:55
  • Vector examples | Vectors and spaces | Linear Algebra | Khan Academy25:33
  • Proving vector dot product properties | Vectors and spaces | Linear Algebra | Khan Academy10:45
  • Column space of a matrix | Vectors and spaces | Linear Algebra | Khan Academy10:40
  • Dot and cross product comparison/intuition | Vectors and spaces | Linear Algebra | Khan Academy19:14
  • Null space 3: Relation to linear independence | Vectors and spaces | Linear Algebra | Khan Academy11:35
  • Basis of a subspace | Vectors and spaces | Linear Algebra | Khan Academy19:00
  • Introduction to matrices11:51
  • Matrix multiplication (part 1)13:41
  • Matrix multiplication (part 2)14:37
  • 3-variable linear equations (part 1)08:02
  • Solving 3 Equations with 3 Unknowns15:26
  • Linear Algebra: Introduction to Vectors16:31

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