Machine Learning Field of study: Physics
Programme code: W4-S2FZA22.2025

Module name: Machine Learning
Module code: W4-FZ-BP-S2-2-25-04
Programme code: W4-S2FZA22.2025
Semester: summer semester 2025/2026
Language of instruction: English
Form of verification: course work
ECTS credits: 6
Purpose and description of the content of education:
In the second-degree physics studies, the subject "Machine Learning" provides an introduction to advanced methods of data analysis and artificial intelligence in the context of physics. The aim of this course is to acquaint students with the latest machine learning techniques and their applications in physics. During the classes, various machine learning techniques are discussed, including regression, classification, and clustering models. Students also learn about deep neural networks, methods for dimensionality reduction of data, and model optimization. Special emphasis is placed on practical applications in physics, such as data analysis from large-scale physical experiments, forecasting experimental results, or discovering hidden patterns in measurement data. This subject enables students to enhance their analytical skills and gain practical experience in utilizing advanced machine learning techniques in the context of physics.
List of modules that must be completed before starting this module (if necessary): not applicable
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
knows the basics of computational and IT techniques supporting the work of a physicist and understands their limitations [E1]
 KF_W07 [5/5]
knows mathematical formalism useful in constructing and analysing physical models of medium complexity; understands the consequences of using approximate methods [E2]
 KF_W06 [3/5]
can use a mathematical apparatus to solve physical problems of medium complexity [E3]
 KF_U02 [3/5]
is able to professionally discuss the issue in question [E4]
 KF_K07 [4/5]
Form of teaching Number of hours Methods of conducting classes Assessment of the learning outcomes Learning outcomes
laboratory classes [FZ1] 45 Laboratory exercise / experiment [e01]  course work E1 E2 E3 E4
The student's work, apart from participation in classes, includes in particular:
Name Category Description
Literature reading / analysis of source materials [a02] Preparation for classes
reading the literature indicated in the syllabus; reviewing, organizing, analyzing and selecting source materials to be used in class
Developing practical skills [a03] Preparation for classes
activities involving the repetition, refinement and consolidation of practical skills, including those developed during previous classes or new skills necessary for the implementation of subsequent elements of the curriculum (as preparation for class participation)
Getting acquainted with the syllabus content [b01] Consulting the curriculum and the organization of classes
reading through the syllabus and getting acquainted with its content
Studying the literature used in and the materials produced in class [c02] Preparation for verification of learning outcomes
exploring the studied content, inquiring, considering, assimilating, interpreting it, or organizing knowledge obtained from the literature, documentation, instructions, scenarios, etc., used in class as well as from the notes or other materials/artifacts made in class
Implementation of an individual or group assignment necessary for course/phase/examination completion [c03] Preparation for verification of learning outcomes
a set of activities aimed at performing an assigned task, to be executed out of class, as an obligatory phase/element of the verification of the learning outcomes assigned to the course
Analysis of the corrective feedback provided by the academic teacher on the results of the verification of learning outcomes [d01] Consulting the results of the verification of learning outcomes
reading through the academic teacher’s comments, assessments and opinions on the implementation of the task aimed at checking the level of the achieved learning outcomes
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)