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Machinations Essentials
Rating: 4.5 out of 5(55 ratings)
763 students

Machinations Essentials

Learn the fundamentals about Machinations, how to create diagrams, run simulations and solve problems in your systems
Last updated 10/2024
English

What you'll learn

  • Basics of Machinations
  • How to build Machinations diagrams
  • Simulation steps and resources
  • Run simulations and predictions
  • Solve problems using Machinations models
  • Using pools, resource connections, sources and converters
  • Adding randomness to models
  • How to use charts

Course content

4 sections40 lectures52m total length
  • Introduction1:33

Requirements

  • No experience in simulation models or systems needed. You will learn everything you need to know about simulations and Machinations

Description

Welcome to the Machinations Essentials course!

You are going to look at the basics of Machinations and create your first diagram working on a Loot and Craft project. You will understand how to use Machinations to analyze and create models to solve problems and make informed decisions. By the end of this course, you will have a good comprehension of the most important components, resources, steps, simulations and predictions.


In the first lesson you will learn the basics of Machinations to understand how simulation models work and how predictions can help you make informed decisions.


In the second lesson you will create your first Machinations project, in which you are going to design, simulate and analyze a model for a basic loot and craft system. This covers the basic components and skills required to build a simple Machinations diagram.


At the end of the course you can take a test to assess your knowledge about Machinations, simulations and the components.


Overall, in this course we will cover the following topics:

  • Simulation models and abstraction

  • Steps

  • Resources

  • Performing a preliminary analysis: defining data, results, steps, runtime and resources

  • Running simulations with interactive plays

  • Executing predictions to extrapolate results

  • Pools

  • Sources

  • Resource connections

  • Randomness: dice throws and random functions

  • Converters

  • Triggers: automatic and passive

  • Diagram styles and best practices

  • Charts

Who this course is for:

  • Game designers
  • Token engineers
  • Product managers
  • Data analysts and scientists
  • Process owners