Colocamos abaixo (algumas) aulas da Khan Academy (Álgebra Linear) e do MIT, Prof. Strang.

- Introduction to Vectors (Khan Academy)
- Visually understanding basic vector operations (Khan Academy)
- Parametric Representations of Lines in R2 and R3 (Khan Academy)
- Matrices to solve a vector combination problem (Khan Academy) Using matrices to figure out if some combination of 2 vectors can create a 3rd vector
- Linear Combinations and Span (Khan Academy) Understanding linear combinations and spans of vectors
- Introduction to Linear Independence (Khan Academy)
- More on linear independence(Khan Academy)
- Span and Linear Independence Example (Khan Academy) Determining whether 3 vectors are linearly independent and/or span R3

- 3-variable linear equations (part 1) (Khan Academy) Visual intuition of a 3-variable linear equation.
- Resolvendo Sistemas Lineares Geometria dos Sistemas Lineares (MIT)
- Escalonamento Eliminação com Matrizes (MIT)
- Análise Pós-Escalonamento Resolvendo Ax=0 (MIT) Resolvendo Ax=b (MIT)
- Solving 3 Equations with 3 Unknowns(Khan Academy)
- Matrices: Reduced Row Echelon Form 1 (Khan Academy) Solving a system of linear equations by putting an augmented matrix into reduced row echelon form
- Matrices: Reduced Row Echelon Form 2 (Khan Academy) Another example of solving a system of linear equations by putting an augmented matrix into reduced row echelon form
- Matrices: Reduced Row Echelon Form 3 (Khan Academy) And another example of solving a system of linear equations by putting an augmented matrix into reduced row echelon form
- Matrix Vector Products (Khan Academy) Defining and understanding what it means to take the product of a matrix and a vector

- Linear Combinations and Span (Khan Academy) Understanding linear combinations and spans of vectors
- Introduction to Linear Independence (Khan Academy)
- More on linear independence(Khan Academy)
- Span and Linear Independence Example (Khan Academy) Determining whether 3 vectors are linearly independent and/or span R3
- Linear Subspaces(Khan Academy) Introduction to linear subspaces of Rn
- Subespaços Transpostas, Permutações e Espaços R^n (MIT)
- Basis of a Subspace(Khan Academy) Understanding the definition of a basis of a subspace
- Dependência e Independência Linear, Base e Dimensão: Independência, Base e Dimensão (MIT)
- Proof: Any subspace basis has same number of elements (Khan Academy)

- A more formal understanding of functions (Khan Academy)
- Vector Transformations(Khan Academy)
- Linear Transformations(Khan Academy)
- Matrix Vector Products as Linear Transformations(Khan Academy)
- Linear Transformation Examples: Scaling and Reflections (Khan Academy)
- Linear Transformation Examples: Rotations in R2(Khan Academy)
- Rotation in R3 around the X-axis(Khan Academy)
- Introduction to the Null Space of a Matrix(Khan Academy) Showing that the Null Space of a Matrix is a valid Subspace
- Null Space 2: Calculating the null space of a matrix(Khan Academy)
- Column Space of a Matrix(Khan Academy)
- Null Space and Column Space Basis(Khan Academy)
- Dimension of the Null Space or Nullity(Khan Academy)
- Dimension of the Column Space or Rank (posto) (Khan Academy)
- Espaço Coluna e Núcleo (MIT)
- Compositions of Linear Transformations 1(Khan Academy) Introduction to compositions of Linear Transformations
- Compositions of Linear Transformations 2(Khan Academy) Providing the motivation for definition of matrix products
- Matrix Product Examples(Khan Academy)
- More on multiplying matrices(Khan Academy)
- Inverting Matrices(Khan Academy) Using Gauss-Jordan elimination to invert a 3x3 matrix.
- Example of calculating the inverse of a matrix (Khan Academy)
- Multiplicação de Matrizes e Inversa. Multiplicação de Matrizes e Inversa (MIT)
- Matrices to solve a system of equations (Khan Academy) Using the inverse of a matrix to solve a system of equations.
- Exploring the solution set of Ax=b(Khan Academy) (non homogeneous equations)
- Coordinates with Respect to a Basis(Khan Academy) Understanding alternate coordinate systems
- Change of Basis Matrix (Khan Academy)
- Decomposição SVD (tópico) Decomposição em Valores Singulares (SVD) (MIT)

- Vector Dot Product and Vector Length(Khan Academy)
- Proving Vector Dot Product Properties(Khan Academy) Proving the "associative", "distributive" and "commutative" properties for vector dot products.
- Unit Vectors(Khan Academy) What unit vectors are and how to construct them
- Orthogonal Complements(Khan Academy)
- Complemento Ortogonal Vetores e Subespaços Ortogonais (MIT)
- Introduction to Projections(Khan Academy) Determining the projection of a vector on s line
- Visualizing a projection onto a plane(Khan Academy)
- Expressing a Projection on to a line as a Matrix Vector prod(Khan Academy)
- Projection is closest vector in subspace(Khan Academy)
- Projections onto Subspaces (Khan Academy)
- Subspace Projection Matrix Example(Khan Academy)
- Another Example of a Projection Matrix(Khan Academy)
- Projeção Ortogonal: Projeções nos Sub-espaços (MIT) Prof. Strang
- Mínimos Quadrados: Mínimos Quadrados e Matriz de Projeção (MIT)
- Least Squares Approximation(Khan Academy) The least squares approximation for otherwise unsolvable equations
- Least Squares Examples(Khan Academy)
- Another Least Squares Example (Khan Academy) Using least squares approximation to fit a line to points
- Gram-Schmidt: Matrizes Ortogonais e Gram-Schmidt (MIT)

- Propriedades do Determinante Propriedades dos Determinantes (MIT)
- Determinant and area of a parallelogram(Khan Academy) Realizing that the determinant of a 2x2 matrix is equal to the area of the parallelogram defined by the column vectors of the matrix
- Simpler 4x4 determinant(Khan Academy) Calculating a 4x4 determinant by putting in in upper triangular form first.
- Determinant as Scaling Factor(Khan Academy) Viewing the determinant of the transformation matrix as a scaling factor of regions

- Introduction to Eigenvalues and Eigenvectors (Khan Academy) What eigenvectors and eigenvalues are and why they are interesting
- Example solving for the eigenvalues of a 2x2 matrix(Khan Academy)
- Finding the eigenvectors and eigenspaces of a 2x2 matrix(Khan Academy)
- Eigenvalues of a 3x3 matrix (Khan Academy)
- Eigenvectors and Eigenspaces for a 3x3 matrix(Khan Academy)
- Autovalores e Autovetores: Autovalores e Autovetores (MIT)
- Diagonalização e Potências de Matriz: Diagonalização e Potências de A (MIT)
- Matriz Simétrica e Positivo Definida: Matrizes Simétrica e Positivo Definidas (MIT)