Search results for: AGENT UBEZPIECZENIOWY

• Systemy Agentowe - 2022

  e-Learning Courses

  • M. Matuszek

  {mlang pl}Systemy Agentowe{mlang}{mlang en}Agent Systems{mlang}

• Systemy Agentowe - 2023

  e-Learning Courses

  • M. Matuszek

  {mlang pl}Systemy Agentowe{mlang}{mlang en}Agent Systems{mlang}

• Statystyka ubezpieczeniowa

  e-Learning Courses

  • M. F. Kaszubowski

• Statystyka ubezpieczeniowa

  e-Learning Courses

  • M. F. Kaszubowski

• Statystyka ubezpieczeniowa 2023

  e-Learning Courses

  • M. F. Kaszubowski

• Matematyka finansowa i ubezpieczeniowa

  e-Learning Courses

  • K. Zawadzki

• Statystyka ubezpieczeniowa (2023 online)

  e-Learning Courses

  • M. F. Kaszubowski

• Statystyka ubezpieczeniowa (2023 niestacjonarne)

  e-Learning Courses

  • M. F. Kaszubowski

• 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

• 22-23 Matematyka finansowa i ubezpieczeniowa

  e-Learning Courses

  • E. Mazurek-Krasodomska
  • M. Potrykus

• 23-24 Matematyka finansowa i ubezpieczeniowa online

  e-Learning Courses

  • E. Mazurek-Krasodomska

• 23-24 Matematyka finansowa i ubezpieczeniowa N

  e-Learning Courses

  • E. Mazurek-Krasodomska

• 23-24 Matematyka finansowa i ubezpieczeniowa S

  e-Learning Courses

  • E. Mazurek-Krasodomska

• Statystyka ubezpieczeniowa Analityka gospodarcza (WZiE), II stopnia, niestacjonarne, 2023/2024 - zimowy (obecnie sem. 2)

  e-Learning Courses

  • M. F. Kaszubowski
  • K. Flisikowski

• Statystyka ubezpieczeniowa Analityka gospodarcza (WZiE), II stopnia, stacjonarne, 2023/2024 - zimowy (obecnie sem. 2)

  e-Learning Courses

  • M. F. Kaszubowski
  • K. Flisikowski

• Statystyka ubezpieczeniowa Analityka gospodarcza (WZiE), II stopnia, niestacjonarne (on-line), 2023/2024 - zimowy (obecnie sem. 2)

  e-Learning Courses

  • M. F. Kaszubowski
  • K. Flisikowski

• Are you the change? Exploring citizen engagement for Smart Sustainable Cities

  e-Learning Courses

  • M. Ciesielska

  The purpose of this course is to explore citizen engagement in the context of smart, sustainable cities, with the goal of providing students with an understanding of the principles and practices involved in urban landscaping. Throughout the course, students will explore key concepts and practical applications across various domains, from understanding the principles of citizen engagement to analyzing the role of digital technologies...