Навчальні курси Agent Based Modeling

Навчальні курси Agent Based Modeling

Місцеві, інструктор з навчання живий агент на основі моделювання навчальних курсів демонструють через інтерактивні практичний практиці основи агента основі моделювання.

Агент основі моделювання підготовки доступна як "на місці навчання" або "дистанційне навчання в прямому ефірі". На місці навчання в прямому ефірі може здійснюватися на місцевому рівні в україні або в Неbleprog корпоративні навчальні центри в україні. Дистанційне навчання в прямому ефірі здійснюється шляхом інтерактивного, віддаленого робочого стола.

Nobleпрога-ваш місцевий навчальний провайдер

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Agent Based Modeling Підкатегорії

Agent Based Modeling Зміст курсу

Назва курсу
Тривалість
Огляд
Назва курсу
Тривалість
Огляд
14 годин
This instructor-led, live training in україні (online or onsite) is aimed at investigators who wish to use Mesa to create Agent Based Models in a Python environment.

By the end of this training, participants will be able to:

- Install and configure the development environment needed to start modeling in Python.
- Quickly create an agent-based model using Mesa's built-in core components.
- Expand the complexity of the model.
- Visualize agent activity in real-time inside a browser.
- Analyze the results of the model interactively using Python data analysis tools.
- Integrate the model with other Python systems such as machine learning applications.
28 годин
The Repast Suite is a family of advanced, free, and open source agent-based modeling and simulation libraries that have collectively been under continuous development for over 10 years. This four day course in україні (online or onsite) explains in detail how to create simulation for agent-based systems using the Repast environment.

Course Objectives

- Introduce participants to principles and concepts of agent-based modeling and simulation.
- Develop participants’ capacity to read and understand agent modeling programming code.
- Equip participants with knowledge, so they understand the importance of accurate and precise modeling.
- Increase the participants’ understanding of systems of their own using the Agent-based simulation.
- Develop a better capacity to use and code agent-based systems using repast, reLogo.

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