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(in Polish) 1 rok 2 stopnia sem. letni Informatyka spec. Technologie Internetowe i Mobilne (course group defined by Institute of Computer Science)

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Course group: (in Polish) 1 rok 2 stopnia sem. letni Informatyka spec. Technologie Internetowe i Mobilne
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2023 - Academic year 2023/2024
2024 - Academic year 2024/2025
(there could be semester, trimester or one-year classes)
Actions
2023 2024
510-IS2-1BDPA-23
Classes
Academic year 2023/2024
  • Laboratory - 30 hours
  • Lecture - 15 hours
Academic year 2024/2025
  • Laboratory - 30 hours
  • Lecture - 15 hours
Groups

Brief description

(in Polish) Architektury i typy

danych. Algorytmy przetwarzania danych w dużej skali. Techniki optymalizacji

przetwarzania danych. Systemy rozproszonego przechowywania i przetwarzania danych. Przetwarzanie danych w chmurze.

Course page
510-IS2-1TXP-23
Classes
Academic year 2023/2024
  • Laboratory - 30 hours
  • Lecture - 15 hours
Academic year 2024/2025
  • Laboratory - 30 hours
  • Lecture - 15 hours
Groups

Brief description

The aim of the course is to familiarize students with the following formats: XML, JSON, YAML, CBOR, etc., and to develop the skills of creating documents in these languages.

Course page
510-IS2-1GUM-23
Classes
Academic year 2023/2024
  • Laboratory - 30 hours
  • Lecture - 15 hours
Academic year 2024/2025
  • Laboratory - 30 hours
  • Lecture - 15 hours
Groups

Brief description

(in Polish) Definicja głębokich sieci neuronowych jako specyficznego

paradygmatu uczenia maszynowego, optymalizacji i modelowania. Definicja parametrów i hiperparametrów modeli. Omówienie modułowych charakterystyk modeli głębokich. Opis najważniejszych i najczęściej używanych elementów głębokich sieci neuronowych, w tym warstw gęstych, splotowych, agregujących, fałdujących, redukujących i resztkowych. Komponenty nieliniowe i normalizujące. Funkcja straty i charakterystyka najczęściej stosowanych funkcji straty. Uczenie się poprzez hetero- i autoasocjację. Implementacja algorytmów głębokich sieci neuronowych. Głębokie modele uczenia się bez nadzoru, w szczególności do analizy skupień. Modele generatywne (GAN).

Course page
510-IS2-1JAI-23
Classes
Academic year 2023/2024
  • Foreign language class - 30 hours
Academic year 2024/2025
  • Foreign language class - 30 hours
Groups

Brief description

Using the English language in IT professional situations, as well as developing the ability to understand and use advanced IT terminology (computer networks, operating systems, electronic devices, data and computer systems security, communication systems, computer engineering, development of information technology).

Course page
510-IS2-1MSR-23
Classes
Academic year 2023/2024
  • Laboratory - 15 hours
  • Lecture - 30 hours
Academic year 2024/2025
  • Laboratory - 15 hours
  • Lecture - 30 hours
Groups

Brief description

Course contents:

Fuzzy sets, fuzziness and randomness, types of membership functions of fuzzy sets, arithmetic operations on fuzzy numbers, extension principle, basic fuzzy models, fuzzy neural models, fuzzy control using fuzzy models.

The aim of the course is to familiarize students with fuzzy modelling and analysis.

Course page
510-IS2-1MOR-23
Classes
Academic year 2023/2024
  • Laboratory - 30 hours
  • Lecture - 15 hours
Academic year 2024/2025
  • Laboratory - 30 hours
  • Lecture - 15 hours
Groups

Brief description

(in Polish) Przedmiot ma za zadanie wprowadzenie studentów w zagadnienia nowoczesnych obliczeń naukowych realizowanych przy pomocy akceleratorów opartych na procesorach graficznych.

W ramach wykładu zostaną omówione podstawy teoretyczne a w trakcie ćwiczeń studenci zdobędą praktyczną wiedzę w zakresie analizy algorytmów obliczeniowych, wyodrębniania kerneli obliczeniowych i ich przenoszenia na koprocesor graficzny z wykorzystaniem języka CUDA.

Course page
510-IS2-1TMO-23
Classes
Academic year 2023/2024
  • Laboratory - 15 hours
  • Lecture - 15 hours
Academic year 2024/2025
  • Laboratory - 15 hours
  • Lecture - 15 hours
Groups

Brief description

Course objectives: The aim of the course is to familiarize students with contemporary mobile technologies.

Course contents: positioning and navigation of mobile users; global positioning system (GPS); cellular systems - architecture and principles of operation of the system; wireless systems; complex mobile processing problems; mobile IP; wireless LAN.

Course page
510-IS2-1TMUL-23
Classes
Academic year 2023/2024
  • Laboratory - 15 hours
  • Lecture - 15 hours
Academic year 2024/2025
  • Laboratory - 15 hours
  • Lecture - 15 hours
Groups

Brief description

Aims and objectives: The aim of the course is to familiarize students with the most popular applications supporting the development of multimedia applications. Assumptions of the course allow to acquire and broaden knowledge from hardware and software configuration of systems for multimedia applications and computer applications as a tool for creating interactive presentations and demonstrations.

Multimedia as a form of communication - multimedia applications. Multimedia devices. Internet image and sound transmission in real time - videoconferencing. Multimedia data compression.

Entropy. Redundancy. Lossy compression - standard JPEG, MPEG Video, MPEG Audio. Lossless compression - Huffman method, Huffman tree construction. Dictionary methods (LZ). Graphics, audio, video coding systems - formats. Digital recording and processing of sound and video sequences. Computer animations, video capturing. Multimedia applications, tutorials.

Course page
510-IS2-1SE-23
Classes
Academic year 2023/2024
  • Laboratory - 15 hours
  • Lecture - 15 hours
Academic year 2024/2025
  • Laboratory - 15 hours
  • Lecture - 15 hours
Groups

Brief description

Using rules and facts to representing knowledge, inferring, and making decisions. The architecture of a system that uses a rule engine. Applications of the rule-based approach. Expert systems and knowledge-based systems versus business-rule systems and BRMS software. Technologies for developing rule-based and expert systems. Methods for gathering knowledge and constructing rules and facts. Problems with rule processing: conflict resolution strategies and uncertainty modeling. Hybrid AI systems that use explicit representations of knowledge.

This subject is aimed at familiarizing students with

- working principles of expert (knowledge-based) systems and rule-based systems,

- application fields of expert/knowledge/rule-based systems,

and at developing student's skills in designing and implementing practical rule-based systems by using selected technologies.

Course page
ul. Świerkowa 20B, 15-328 Białystok tel: +48 85 745 70 00 (Centrala) https://uwb.edu.pl contact accessibility statement site map USOSweb 7.1.2.0-4 (2025-05-14)