Search results for: ARCHITECTURES

• Computer Networks EN 2022

  e-Learning Courses

  • J. Woźniak
  • J. Grochowski
  • K. Gierłowski

  The student becomes familiar with the network layered logical architectures, classifies the basic problems of network communication and identifies and analyzes selected protocols and mechanisms of LAN and WAN (IP) networks.

• Computer Networks EN 2023

  e-Learning Courses

  • M. Hoeft
  • J. Woźniak
  • J. Grochowski
  • K. Gierłowski

  The student becomes familiar with the network layered logical architectures, classifies the basic problems of network communication and identifies and analyzes selected protocols and mechanisms of LAN and WAN (IP) networks.

• Biznesowe aplikacje wielkoskalowe

  e-Learning Courses

  • K. Cwalina

  Zapoznanie z architekturami biznesowych aplikacji wielkoskalowych i narzędziami do ich wytwarzania. Overview of design patterns, architectures, and tools used for design and development of large-scale enterprise applications.

• Biznesowe aplikacje wielkoskalowe - 2023/2024

  e-Learning Courses

  • K. Cwalina

  Zapoznanie z architekturami biznesowych aplikacji wielkoskalowych i narzędziami do ich wytwarzania. Overview of design patterns, architectures, and tools used for design and development of large-scale enterprise applications.

• 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.

• Deep neural networks for data analysis 24/25

  e-Learning Courses

  • J. Cychnerski
  • K. Draszawka

  This course covers introduction to supervised machine learning, construction of basic artificial deep neural networks (DNNs) and basic training algorithms, as well as the overview of popular DNNs architectures (convolutional networks, recurrent networks, transformers). The course introduces students to popular regularization techniques for deep models. Besides theory, large part of the course is the project in which students apply...