Obligatory courses for 1st year Machine Learning (course group defined by Faculty of Mathematics, Informatics, and Mechanics)
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2023Z - Winter semester 2023/24 2023L - Summer semester 2023/24 2024Z - Winter semester 2024/25 2024L - Summer semester 2024/25 (there could be semester, trimester or one-year classes) |
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| 1000-317bBUM |
 
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Classes
Winter semester 2023/24
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Brief description
The goal of the course is to present the set of elementary notions of machine learning necessary to understand contemporary, advanced techniques of machine learning as well to instil the programming techniques necessary to efficiently use them. |
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| 1000-317bBIM |
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Classes
Winter semester 2023/24
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Brief description
The goal of the course is to present the set of common mathematical notions necessary to understand contemporary techniques of machine learning as well as to instil the mathematical apparatus necessary to efficiently use them. |
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| 1000-317bDNN |
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Classes
Winter semester 2023/24
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Brief description
The goal of the course is to show usage cases for deep neural networks. During the course state-of-the-art techniques, algorithms and tools will be presented. Among others two main blocks of the course will concern image classification and text processing. |
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| 1000-317bIII |
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Classes
Winter semester 2023/24
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Brief description
The classes are a platform where students present ideas of potential business. The students’ presentations are complemented by lectures concerning the legal and economical issues related to running a business in informatics. |
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| 1000-318bNLP | n/a |
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Classes
Summer semester 2023/24
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Brief description
The goal of the course is to familiarize students with the theory, methodology, resources and tools for natural language processing. Lectures concern issues of computational linguistics (morphological, syntactic and semantic analysis), information extraction, text classification and automatic summarization of documents. The course will discuss the tools and language-specific issues for English and Polish. Knowledge of the theory of formal grammars and knowledge of machine learning techniques will be helpful. |
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| 1000-318bRL | n/a |
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Classes
Summer semester 2023/24
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Brief description
The goal of the course is to present modern techniques and algorithms of reinforcement machine learning, with particular emphasis on model-free, model-based and exploration methods. |
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| 1000-317bRC |
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Classes
Winter semester 2023/24
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Brief description
The aim of the course is to familiarize students with the practical knowledge needed to operate in the field of robotics. Three sections will be presented during the course: * machine vision from the point of view of robotics, * elements of control theory, * basics of robotics. |
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| 1000-317bSML |
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Classes
Winter semester 2023/24
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Brief description
The goal of the course is to introduce fundamental notions and statistical tools used in machine learning such as linear, logistic and multivariate regression, classifiers, dimension reduction methods, bayesian methods. |
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| 1000-318bVR | n/a |
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Classes
Summer semester 2023/24
Groups
Brief description
The goal of the course is to present deep learning architectures as well as to teach implementation, training and debugging own neural networks dedicated to visual recognition. Students gain theoretical knowledge, information on the state of the current research in the domain and obtain practical skills in visual recognition. |
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