Applied Numerical Methods for Python for Electrical Engineers

Catalog description

Description: This course is an introduction to numerical linear algebra and related numerical methods. Topics include direct and iterative methods for linear systems, eigenvalue decompositions and QR/SVD factorizations, stability and accuracy of numerical algorithms, the IEEE floating-point standard, sparse and structured matrices, and an introduction to machine learning/AI and linear algebra software. Other topics may include nonlinear optimization, numerical integration and differentiation, FFTs, and sensitivity analysis. Problem sets will involve heavy use of the Python environment (little or no prior experience required; you will learn as you go).