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2026 Intro to Agent-Based Modeling Simulation AI in NetLogo
Rating: 3.5 out of 5(77 ratings)
308 students

2026 Intro to Agent-Based Modeling Simulation AI in NetLogo

Learn Agent-Based Modeling Artificial Intelligence paradigm and implement it on virus spread simulation in COVID times.
Created byJan Pastorek
Last updated 4/2026
English

What you'll learn

  • 1 Practical application of Agent-Based modeling ( virus spread simulation - e.g. COVID-19 )
  • Agent-Based modeling AI and its applicability in different fields
  • Visualize plots in NetLogo
  • NetLogo language
  • Storytelling through simulation
  • Put NetLogo simulation models on Website

Course content

4 sections12 lectures1h 1m total length
  • Course Outline + Big Picture1:55
  • Introduction and Overview5:09
  • Installing NetLogo2:03
  • Getting to know NetLogo environment1:33

Requirements

  • Just basics of programming needed (defining variables, functions, if-statements) - I provide you with link to course with these basics, you can go through it in less than 30 minutes
  • Willingness to learn :)

Description

Discover the "Other" AI: Master Agent-Based Modeling

When most people talk about Artificial Intelligence, they are only talking about Machine Learning and Large Language Models such as ChatGPT. But there is a hidden, incredibly powerful branch of AI that often goes unnoticed: Agent-Based Modeling (ABM). If you are fascinated by AI but intimidated by heavy mathematics, this course is your perfect entry point.

Unlike traditional machine learning, Agent-Based Modeling is elegantly simple. You don't need a background in calculus or linear algebra. Instead, you define simple rules for individual "agents," place them in a virtual environment, and watch as stunning, complex, emergent behaviors unfold right before your eyes.

What Can You Build with Agent-Based Modeling?

Because ABM mimics real-world interactions, it has led to groundbreaking insights across the social sciences and STEM fields. In this course, you will learn how to simulate real-world phenomena, such as:

  • Society & Epidemiology: Model how a virus spreads through a population or how different groups of people interact.

  • Ecology & Environment: Simulate natural disasters like the spread of forest fires or analyze predator-prey dynamics.

  • Physics & Chemistry: Recreate complex chemical reactions and physical phenomena on your screen.

Doesn’t that sound amazing?

What You Will Learn

We will be coding in NetLogo, one of the most popular, powerful, and accessible environments for Agent-Based Modeling. By the end of this course, you will have a deep understanding of a completely different AI paradigm.

Inside the course, we will cover:

  • The Core Theory: Understand the fundamentals of Agent-Based AI and emergent behavior.

  • Hands-On Project: Build a complete, working simulation of a virus outbreak from scratch.

  • Data Storytelling: Learn how to translate your simulation results into compelling narratives.

  • Web Deployment: Discover how to put your simulations on a website to share with the world.

Is This Course for You?

If you’re ready to take on a brand-new challenge, step outside the traditional machine learning box, and learn a powerful AI technique that allows you to build incredible things with minimal math, then this course is exactly what you need.

Enroll today and discover what you can create. See you in class!

Instructor's Pro-Tips for Success

To get the absolute most out of this course, I highly recommend the following:

  1. Learn by Doing: Don't just watch the videos! Write the code yourself alongside me. You learn coding by coding. :)

  2. Take Handwritten Notes: I will provide all my presentation slides. Jotting down physical notes as you review them will dramatically improve your retention of the theory.

  3. Adjust the Speed: Feel free to watch the theory lectures at 1.5x speed, and slow down to 1.25x or normal speed during the coding sections so you can follow along comfortably.

Who this course is for:

  • Beginners in Agent-Based modeling
  • Beginners in Simulating Complex systems
  • Social scientists
  • Beginners in Programming
  • Journalists
  • Ecologists
  • Physicists
  • Chemists
  • Biologists