Short Course Description
Credit Points: 3
Part 1: Linear algebra
Positive definite matrices, matrix decompositions, eigenvalues and dynamical systems, minimum principles, fundamentals of linear algebra. Using linear algebra for solving statics and dynamics of spring-mass systems, electrical networks and trusses.
Part 2: selected topics in optimization and machine learning
Optimization: minimum problems, Lagrange multipliers, Gradient Descent and Stochastic Gradient Descent.
Machine learning: neural networks, convolutional neural networks, recurrent neural networks.
Full syllabus will be available to registered students only
