We discuss a set of topics that are important for the understanding of modern data science but that are typically not taught in an introductory ML course. In particular we discuss fundamental ideas and techniques that come from probability, information the ...
Machine learning and data analysis are becoming increasingly central in many sciences and applications. This course concentrates on the theoretical underpinnings of machine learning. ...
The course establishes the concepts of statistical analysis, probability theory, and data analysis. This includes standard statistical tests, correlation analysis and experimental design. It introduces computational statistical methods to analyse large dat ...
State-of-the-art surface/thin film characterization methods of polycrystalline/nano/amorphous materials. Selected topics from thin film X-ray diffraction (GIWAXS, GISAXS, PDF), electronic and optical spectroscopy (XPS, AES, SERS, TERS), scanning probe and ...
The course relates on the use of electromagnetic (X-Ray) and corpuscular (electrons) radiations for physical and chemical analysis of solid materials. ...
This course gives the basics for understanding nanotechnology from an engineer's perspective: physical background, materials aspects and scaling laws, fabrication and imaging of nanoscale devices. ...
Life has emerged on our planet from physical principles such as molecular self-organization, thermodynamics, stochastics and iterative refinement. This course will introduce the physical methods to study life and will discuss the quantitative and physical ...