Teaching
Teaching
Models for Continuous Optimization and Applications (160h): linear programming, linear regression, spline regression, and nonlinear optimization methods (Bachelor second year).
Data Science (100h): basic notions of statistics and probability theory for descriptive statistics, inference and supervised classification (Bachelor first year).
Algorithmic I (80h): introduction to algorithms (basic proofs of validity, termination, and complexity), and an introduction to graph theory (Bachelor second year).
Programming Elements II (40h): introduction to C (Bachelor first year).