Search results for: DATA PROCESSING ALGORITHMS

• WETI (Data Engineering) - Mathematics 2023/24 (E.Kozłowska-Walania)

  e-Learning Courses

  • M. M. Musielak
  • E. Kozłowska-Walania

• D. Zalewska 3 Data Engineering , 3s, C1 24/25z

  e-Learning Courses

  • U. Kamińska
  • I. Mokwa-Tarnowska
  • J. Wielgus
  • E. Wawoczna
  • D. Zalewska

• DATA MINING (Field of study: Economic analytics 1st semester) -2022

  e-Learning Courses

  • N. Rizun

• WETI - Data Engineering gr.2 - Math 2019/20 (A.Brękiewicz-Sieg)

  e-Learning Courses

  • A. Brękiewicz-Sieg

• [AEiE, ITiT] Scientific methods of computer data analysis and presentation - 2022/2023

  e-Learning Courses

  • T. E. Berezowski

  {mlang pl} Dyscyplina: AEiE, ITiT Zajęcia obowiązkowe dla doktorantów II roku Prowadzący:  Tomasz Berezowski Liczba godzin: 30 Forma zajęć: wykład/projekt/seminarium {mlang} {mlang en} Discipline: AEiE, ITiT Obligatory course for 2nd-year PhD students Academic teacher: Tomasz Berezowski Total hours of training: 30 teaching hours Course type: Lecture/project/seminar {mlang}      

• [AEEiTK, ITiT] Scientific methods of computer data analysis and presentation - 2023/2024

  e-Learning Courses

  • T. E. Berezowski

  {mlang pl} Dyscyplina: AEiE, ITiT Zajęcia obowiązkowe dla doktorantów II roku Prowadzący:  Tomasz Berezowski Liczba godzin: 30 Forma zajęć: wykład/projekt/seminarium {mlang} {mlang en} Discipline: AEiE, ITiT Obligatory course for 2nd-year PhD students Academic teacher: Tomasz Berezowski Total hours of training: 30 teaching hours Course type: Lecture/project/seminar {mlang}      

• [AEEiTK, ITiT] Scientific methods of computer data analysis and presentation 2024/2025

  e-Learning Courses

  • T. E. Berezowski

  {mlang pl} Dyscyplina: AEiE, ITiT Zajęcia obowiązkowe dla doktorantów II roku Prowadzący:  Tomasz Berezowski Liczba godzin: 30 Forma zajęć: wykład/projekt/seminarium {mlang} {mlang en} Discipline: AEiE, ITiT Obligatory course for 2nd-year PhD students Academic teacher: Tomasz Berezowski Total hours of training: 30 teaching hours Course type: Lecture/project/seminar {mlang}      

• Benjamin Sempek, WETI+WZIE, Data Engineering, st I, sem2, 22/23l

  e-Learning Courses

  • U. Kamińska
  • I. Mokwa-Tarnowska
  • J. Wielgus
  • E. Wawoczna

• W. Zbirohowski-Kościa WZiE i WETI, Data Eng, I st, sem 2, 21/22l

  e-Learning Courses

  • W. Zbirohowski-Kościa
  • U. Kamińska
  • I. Mokwa-Tarnowska
  • J. Wielgus
  • E. Wawoczna

• Witold Zbirohowski-Kościa, ZiE i ETI, Data Engineering, I st, sem 5, 21/22z

  e-Learning Courses

  • W. Zbirohowski-Kościa
  • U. Kamińska
  • I. Mokwa-Tarnowska
  • J. Wielgus
  • E. Wawoczna

• Małgorzata Piechocińska WETI+WZiE Inż. Danych/Data Engineering I st. 2 sem. 22/23 l

  e-Learning Courses

  • J. Nieszczółkowski
  • U. Kamińska
  • I. Mokwa-Tarnowska
  • J. Wielgus
  • E. Wawoczna
  • M. Piechocińska

• Seminarium dyplomowe / Projekt dyplomowy inżynierski / Diploma thesis 2 - Inżynieria Danych / Data Engineering - sem. 7 - 2024/2025

  e-Learning Courses

  • A. M. Trzaskowska

• Seminarium dyplomowe / Projekt dyplomowy inżynierski / Diploma thesis 1 - Inżynieria Danych / Data Engineering - sem. 6 - 2023/2024

  e-Learning Courses

  • A. M. Trzaskowska

• Zaawansowane Przetwarzanie Sygnałów - angielski - Nowy

  e-Learning Courses

  • A. Szewczyk
  • J. Smulko

  Lecture presents development of advanced signal processing techniques. Seminar, after the lectures, considers selected issues/subjects of signal processing techniques presented by individual students.

• Environmental Protection in Energetics, PG_00049751, W, PE-ET, sem.1, winter 2023/24

  e-Learning Courses

  Environmental aspects of energy production and processing.

• Environmental Protection in Energetics (PG_00049751), W, PE-ET, sem.1, winter 2023/24

  e-Learning Courses

  • R. Liberacki

  Environmental aspects of energy production and processing.

• Environmental Protection in Energetics (PG_00049751), W, ET, sem.1, winter 2024/2025

  e-Learning Courses

  • R. Liberacki

  Environmental aspects of energy production and processing.

• Team Strategies - sem. 2022/23

  e-Learning Courses

  • T. Białaszewski

  The main aim of the course is to familiarize students with the basic problems in team strategies, such as: the use of the particle swarm optimization algorithms, the ant colony optimization, stochastic distributed searches, algorithms for team strategy, multi-agent systems, modeling intelligent cooperation, simulations of social behavior. The form of passing the course is passing the exam and completing a project task

• Team Strategies - sem. 2023/24

  e-Learning Courses

  • T. Białaszewski

  The main aim of the course is to familiarize students with the basic problems in team strategies, such as: the use of the particle swarm optimization algorithms, the ant colony optimization, stochastic distributed searches, algorithms for team strategy, multi-agent systems, modeling intelligent cooperation, simulations of social behavior. The form of passing the course is passing the exam and completing a project task

• Team Strategies - sem. 2024/25

  e-Learning Courses

  • T. Białaszewski

  The main aim of the course is to familiarize students with the basic problems in team strategies, such as: the use of the particle swarm optimization algorithms, the ant colony optimization, stochastic distributed searches, algorithms for team strategy, multi-agent systems, modeling intelligent cooperation, simulations of social behavior. The form of passing the course is passing the exam and completing a project task

• Przetwarzanie rozproszone

  e-Learning Courses

  • M. Kassjański
  • E. Lubecka

  Foundations and rules of distributed and parallel processing in networked computer systems.

• Intelligent information services 23/24

  e-Learning Courses

  • J. Szymański

  Information retrieval Text categorization Natural language processing

• Przetwarzanie Rozproszone 2021/2022

  e-Learning Courses

  • J. Cychnerski
  • P. Weichbroth
  • A. Domagalska
  • M. Matuszek
  • P. Dryja
  • T. Gajger
  • A. Brzeski
  • J. Kuchta
  • A. Królicka-Gałązka
  • T. Cejrowski
  • S. Olewniczak

  {mlang pl}Przetwarzanie równoległe i rozproszone{mlang}{mlang en}Concurrent and Distributed Processing{mlang}

• Przetwarzanie Rozproszone 2022/2023

  e-Learning Courses

  • J. Cychnerski
  • A. Domagalska
  • M. Matuszek
  • J. Kuchta
  • J. Szłapczyńska
  • A. Królicka-Gałązka

  {mlang pl}Przetwarzanie równoległe i rozproszone{mlang}{mlang en}Concurrent and Distributed Processing{mlang}

• Przetwarzanie Rozproszone 2023/2024

  e-Learning Courses

  • J. Cychnerski
  • A. Domagalska
  • M. Matuszek
  • J. Kuchta
  • J. Szłapczyńska
  • A. Królicka-Gałązka
  • J. Majkutewicz
  • R. Kałaska

  {mlang pl}Przetwarzanie równoległe i rozproszone{mlang}{mlang en}Concurrent and Distributed Processing{mlang}

• Algorytmy Optymalizacji Dyskretnej - ed. 2021/2022

  e-Learning Courses

  • K. Pastuszak

  In real-world applications, many important practical problems are NP-hard, therefore it is expedient to consider not only the optimal solutions of NP-hard optimization problems, but also the solutions which are “close” to them (near-optimal solutions). So, we can try to design an approximation algorithm that efficiently produces a near-optimal solution for the NP-hard problem. In many cases we can even design approximation algorithms...

• Monte Carlo Methods

  e-Learning Courses

  • J. Franz

  This course will introduce the foundations of Monte Carlo simulation methods. Fundamental algorithms will be described. It will be shown how Monte Carlo methods can be used to simulate the transport of energetic particles in condensed matter.

• Monte Carlo Methods - 2023/24

  e-Learning Courses

  • J. Franz

  This course will introduce the foundations of Monte Carlo simulation methods. Fundamental algorithms will be described. It will be shown how Monte Carlo methods can be used to simulate the transport of energetic particles in condensed matter.

• Monte Carlo Methods - 2024/25

  e-Learning Courses

  • J. Franz

  This course will introduce the foundations of Monte Carlo simulation methods. Fundamental algorithms will be described. It will be shown how Monte Carlo methods can be used to simulate the transport of energetic particles in condensed matter.

• Deep Learning Basics 2023/24

  e-Learning Courses

  • K. Draszawka

  A course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.

• Descriptive & mathematical statistics 2019

  e-Learning Courses

  • B. Kochański

  Descriptive Statistics for Data Engineering 2019

• Applications of Geographic Information Systems

  e-Learning Courses

  • M. Kulawiak
  • M. Kulawiak

  First degree studies Data Engineering

• Advanced Nonrelational Databases DE 2022/2023

  e-Learning Courses

  • J. Miler
  • T. Zawadzka
  • W. Waloszek

  The course is addressed to bachelor-students in the field of data engineering in the fifth semester.

• Advanced Nonrelational Databases DE 2023/2024

  e-Learning Courses

  • M. Zawadzki
  • T. Zawadzka
  • W. Waloszek

  The course is addressed to bachelor-students in the field of data engineering in the fifth semester.

• Economics and Organisation of Enterprises - winter term 22/23

  e-Learning Courses

  • M. Popowska

  This course is intended for students of the first semester of Data Engineering (inter-faculty program in English)

• Economics and Organisation of Enterprises - winter term 24/25

  e-Learning Courses

  • M. M. Popowska
  • M. Mustafayev

  This course is intended for students in the first semester of Data Engineering (inter-faculty program in English).

• Economics and Organisation of Enterprises - winter term 23/24

  e-Learning Courses

  • M. M. Popowska
  • M. Mustafayev

  This course is intended for students of the first semester of Data Engineering (inter-faculty program in English)

• Software Engineering 2022/2023

  e-Learning Courses

  Course for Data Engineering, semester 3 Access credentials will be provided during the first lab class.

• Software Engineering 2024/2025

  e-Learning Courses

  • A. Jarzębowicz

  Course for Data Engineering, semester 3 Access credentials will be provided during the first lab class.

• Software Engineering 2023/2024

  e-Learning Courses

  • A. Jarzębowicz

  Course for Data Engineering, semester 3 Access credentials will be provided during the first lab class.

• Technical Physics 2024/25

  e-Learning Courses

  • S. Bielski
  • A. Sbai
  • R. C. Sia

  Field of study: Data Engineering; Subject: Technical physics; Lecture notes and other course materials.

• Basics of Physics_21/22

  e-Learning Courses

  • S. Bielski

  Field of study: Data Engineering; Subject name: Basics of Physics; Webinars, footages, assignments, tests and course materials.

• Basics of Physics_22/23

  e-Learning Courses

  • S. Bielski

  Field of study: Data Engineering; Subject name: Basics of Physics; Webinars, footages, assignments, tests and course materials.

• Basics of Physics_23/24

  e-Learning Courses

  • S. Bielski

  Field of study: Data Engineering; Subject name: Basics of Physics; Webinars, footages, assignments, tests and course materials.

• Głębokie Sieci Neuronowe Do Analizy Danych

  e-Learning Courses

  • T. M. Boiński
  • K. Draszawka

  {mlang pl}Kurs przeznaczony jest dla studentów kierunku Inżynieria Danych.{mlang} {mlang en}Course for Data Analysis students.{mlang}

• European Economic Development 2023

  e-Learning Courses

  • A. Parteka
  • R. Ślosarski

  Main aim of the subject is to transfer knowledge on theoretical and empirical aspects of economic development in Europe.  Key topics: •concepts of economic development, alternative measures of development •factors of economic growth and development (‘determinants of growth’) •history of economic development in Europe •cross-country and cross-regional comparisons •sources: where to find information and data needed for empirical...

• Mathematical Statistics (2022/23)

  e-Learning Courses

  • K. Flisikowski

  Mathematical Statistics - Data Engineering - Karol Flisikowski - winter semester 2022/23

• Projektowanie układów VLSI

  e-Learning Courses

  • A. Bekasiewicz
  • A. Pietrenko-Dąbrowska

  The lecture tackles the problem of VLSI circuits design. In particular, emphasis is put on the physical design stage and more in-depth discussion of its sub-components. The lecture also focus on detailed explanation of selected numerical algorithms that are utilized in the course of physical design. Specialization: Microelectronic Systems

• Nonrelational Databases DE 2024_2025

  e-Learning Courses

  • G. Gołaszewski
  • T. Zawadzka
  • A. Landowska

  This course discusses three types of non-relational databases (i.e., document, graph, and key-value). The course is aimed at students in the 5th semester of data engineering.

• Nonrelational Databases DE 2023_2024

  e-Learning Courses

  • G. Gołaszewski
  • T. Zawadzka

  This course discusses three types of non-relational databases (i.e., document, graph, and key-value). The course is aimed at students in the 5th semester of data engineering.