Search results for: algorithms - Bridge of Knowledge

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Search results for: algorithms

Search results for: algorithms

  • Algorithms and Data Structures 2022

    e-Learning Courses
    • R. Ostrowski
    • K. Manuszewski
    • T. Pikies
    • K. Wereszko
    • A. Jastrzębski
    • M. Jurkiewicz
    • T. Goluch

    WETI, DS, Algorithms and Data Structures

  • Algorithms & Data Structures 2022/23

    e-Learning Courses
    • R. Janczewski
    • K. Manuszewski
    • M. Jurkiewicz

  • Algorithms & Data Structures 23/24

    e-Learning Courses
    • R. Ostrowski
    • K. Manuszewski
    • A. Jastrzębski
    • M. Jurkiewicz
    • T. Goluch

  • Algorytmy równoległe i rozproszone/Parallel and distributed >> algorithms

    e-Learning Courses
    • J. Cychnerski
    • M. Matuszek
    • P. Kaczmarek
    • P. Czarnul

  • Data Structures (Doctoral Studies) - New

    e-Learning Courses
    • K. Goczyła

    The course is designed to provide students with the knowledge regarding basic data structures and associated algorithms used in broad range of applications. Students will also gain knowledge about how to evaluate the quality of algorithms in the context of time and space usage. Additionally, during seminars, students get familiar with biographies of most famous creators of the algorithms.

  • Image Processing in Robotics (2021/2022)

    e-Learning Courses
    • P. Chudziak

    For ISD M.Sc. (II degr.) 2 sem. Participants are to learn image processing algorithms related to transformation, filtration, feature detection (image descriptors), image processing algorithms in robotic industrial systems.

  • Data Structures (Doctoral Studies)

    e-Learning Courses
    • K. Goczyła

    The course covers basic data structures and computer algorithms used in information tehcnology applications. 

  • 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

  • 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.

  • 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.

  • 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

  • Computer controlled systems - 2022/2023

    e-Learning Courses
    • P. Raczyński

    materiały wspierające wykład na studiach II stopnia na kierunku ACR pod tytułem komputerowe systemy automatyki 1. Computer system – controlled plant interfacing technique; simple interfacing and with both side acknowledgement; ideas, algorithms, acknowledge passing. 2. Methods of acknowledgement passing: software checking and passing, using interrupt techniques, using readiness checking (ready – wait lines). The best solution...

  • CCS-lecture-2023-2024

    e-Learning Courses
    • P. Raczyński

    materiały wspierające wykład na studiach II stopnia na kierunku ACR pod tytułem komputerowe systemy automatyki 1. Computer system – controlled plant interfacing technique; simple interfacing and with both side acknowledgement; ideas, algorithms, acknowledge passing. 2. Methods of acknowledgement passing: software checking and passing, using interrupt techniques, using readiness checking (ready – wait lines). The best solution optimization...