Linear Algebra

• Vectors: Operations on Vectors, Orthogonal Vectors, Norm of a vector, Inner product, cosine similarity
• Matrices: Operations like dot product, multiplication, Hadamard product, Linear basis, Transpose, Rank of matrix, Linear mappings, Meaning of matrix multiplication from geometrical context, Inverse of matrix, Eigen Values and Vectors, Principal Component Analysis, Singular Value Decomposition.

Calculus

• Functions, limit of function, derivative, product rule, division rule, chain rule, Partial Derivative, Hessian, Jacobian.

Optimization Techniques

• Linear Programming Problem, Lagrange's Multipliers, Minima and Maxima, Least Squares Method, Gradient Descent, Newton's method

Python options

• Packages: numpy.linalg module, sympy