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Linear equations, matrices, linear programming, sets and counting, probability and statistics.
Methods for obtaining numerical and analytic solutions of elementary differential equations. Applications are also discussed with an emphasis on modeling.
Linear approximation and Taylor’s theorems, Lagrange multiples and constrained optimization, multiple integration and vector analysis including the theorems of Green, Gauss, and Stokes.
An introduction to multivariable calculus through vectors in 3D, curves, functions of several variables, partial derivatives, min/max problems, multiple integration. Vector Calculus not covered.
This is an intensive course on linear algebra, taught at a sophisticated and abstract level.
Linear algebra through eigenvalues, eigenvectors, applications to linear systems, least squares, diagonalization, quadratic forms.
An introduction to linear algebra through eigenvalues and eigenvectors, applications to linear systems, least squares.
Definite and indefinite integrals, techniques of integration, improper integrals, infinite series, applications.
Differential calculus including applications and the underlying theory of limits for functions and sequences.
Analytic geometry, the function concept, polynomials, exponential, logarithms, trigonometric functions, mathematical induction, the theory of equations.