Homework and/or Lab Assignments, Final Exam and/or Project
Prerequisite Courses
Calculus I, Linear Algebra I, Python
Syllabus
Floating point arithmetic,
Stability of algorithms,
Root finding algorithms: Bisection, Newton and Secant methods,
Methods for solving linear systems: Direct methods (LU, Cholesky), Iterative methods (Jacobi, Gauss-Seidel, SOR, Steepest Descent, Conjugate Gradient),
Singular Value Decomposition (SVD) and its applications,
Least Squares problem,
Interpolation and Numerical differentiation,
Algorithms in Optimization,
Monte Carlo methods.
Learning Outcomes
Upon completion of the course the students will be able to:
Have good knowledge of the basic numerical algorithms in the field, their properties, and characteristics.
Computer implementation of the algorithms
Solution of basic applied problems using these algorithms
Very good understanding of their capabilities, limitations, advantages, and disadvantages
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