Machine Learning (OPEN UNI)

The course covers machine learning fundamentals and key linear and nonlinear methods for regression and classification. You’ll learn to build models with good performance and strong generalization. Teaching includes theory lectures and self-paced, auto-graded programming exercises. Grades are based on completed tasks, with additional exercises available for interested students.

Content: Introduction. Mathematical optimization for machine learning. Linear and non-linear models for regression and classification. Feature engineering and optimization. Model validation. Kernel methods, neural networks, tree-based learners.