Deep Learning in five steps
Undergraduate course, Wroclaw University, Faculty of Physics and Astronomy, 2023
Deep Learning in five steps.
Teaching
Specialized Lecture - Applications of deep learning in physics
Undergraduate and graduate course, Wroclaw University, Faculty of Physics and Astronomy, 2022
Short introduction to Physics Informed Neural Networks (PINN)
Obliczenia numeryczne i symboliczne w fizyce (Numerical and Symobolical computations in physics)
Undergraduate course, Wroclaw University, Faculty of Physics and Astronomy, 2021
Numeric and symbolic computations in Wolfram Mathematica.
Theory of elementary particles
Graduate course, Wroclaw University, Faculty of Physics and Astronomy, 2021
Introduction to theory of elementary particles (30h of lecture and 30h of classes). The course consists of:
Machine learning (Specialized Lecture)
Undergraduate and graduate course, Wroclaw University, Faculty of Physics and Astronomy, 2021
It was a short introduction to neural networks (10h of lecture and 10h of labs). The course consists of:
Deep learning in physics
Undergraduate and graduate course, Wroclaw University, Faculty of Physics and Astronomy, 2020
Overview of application of deep learning in physics
Introduction to neural computations
Undergraduate and graduate course, Wroclaw University, Faculty of Physics and Astronomy, 2019
It was an introduction to neural computations. The course covers:
Selected problems of lepton-nucleon scattering (monographic lecture)
Graduate course, Wroclaw University, Faculty of Physics and Astronomy, 2014
Elements of lepton-nucleon electromagnetic interactions