active_inference_101

Active Inference 101: College First Semester

Audience: College undergraduates (first exposure to Active Inference) Estimated files: 248

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Curriculum Statistics

Metric	Value
Courses	4
Modules per Course	8
Total Modules	32
Files per Module	7
Estimated Total Files	248
Target Audience	College undergraduates
Prerequisites	Intro psychology or biology recommended

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Overview

Welcome to Active Inference 101 — your first semester introduction to one of the most powerful unifying theories in cognitive science. Active Inference proposes that all living systems work by constantly predicting and acting to minimize surprise.

This curriculum assumes no prior knowledge of the Free Energy Principle and builds understanding progressively through four complementary lenses.

Courses

#	Course	Perspective	Lab Type
1	Cognitive Science	Mind, brain, and behavior	Thought Experiment
2	Computational Neuroscience	Neural circuits and prediction	Simulation
3	Mathematical Frameworks	Formal models and variational methods	Problem Set
4	Implementation	Code and applications	Coding Lab

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Core Topics

Each course covers the same 8 topics in the same order — the Active Inference "spine":

#	Topic	01 CogSci	02 CompNeuro	03 Math	04 Implementation
1	Systems	Cognitive systems	Neural architectures	Dynamical systems	System design
2	Agents	Embodied agents	Neural agents	Agent formalism	Agent classes
3	Perception	Perceptual inference	Predictive coding	Bayesian inference	Sensor models
4	Cognition	Belief updating	Cortical hierarchies	Variational methods	Inference engines
5	Action	Active inference loop	Motor control	Expected free energy	Control loops
6	Learning	Model learning	Synaptic plasticity	Parameter estimation	Training algorithms
7	Communication	Social cognition	Neural communication	Information theory	Message passing
8	Planning	Goal-directed behavior	Prefrontal planning	Policy optimization	Planning agents

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Learning Pathway

Start Here
    ↓
[01 Cognitive Science] ──→ Conceptual foundation
    ↓
[02 Computational Neuroscience] ──→ Neural grounding
    ↓
[03 Mathematical Frameworks] ──→ Formal precision
    ↓
[04 Implementation] ──→ Hands-on mastery

Recommended path: Work through sequentially. Each course builds on the previous one. If you are strong in math, you may start with Course 03 and then return to Courses 01–02 for context.

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Module Structure

Each module contains 7 files:

File	Purpose
module.md	Core lesson content
questions.md	Study and discussion questions
practice_quiz.md	Self-assessment quiz
lab.md	Hands-on activity
dashboard.html	Interactive review dashboard
README.md	Module overview and navigation
AGENTS.md	Content generation guidelines

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Shared Resources

Resource	Purpose
Glossary	Key terms and definitions
Notation Table	Symbols and notation conventions
References	Reading list and citations
Cross-Course Map	How modules connect across courses
Learning Pathways	Suggested routes through the material
FAQ	Frequently asked questions

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Design Principles

1. Spiral learning: The same 8 topics repeat across all 4 courses at increasing depth
2. Multiple perspectives: Each course teaches the same framework through a different lens
3. Active engagement: Every module includes a lab for hands-on practice
4. Self-assessment: Practice quizzes provide immediate feedback
5. Accessibility: Assumes motivated undergraduates with no prior FEP knowledge

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Directory Map

active_inference_101/
├── README.md              ← You are here
├── AGENTS.md              ← Agent guidelines
├── resources/             ← Shared notation, glossary, references
├── 01_cognitive_science/
│   ├── 01_systems/ … 08_planning/   (8 modules)
├── 02_computational_neuroscience/
│   ├── 01_systems/ … 08_planning/   (8 modules)
├── 03_mathematical_frameworks/
│   ├── 01_systems/ … 08_planning/   (8 modules)
└── 04_implementation/
    ├── 01_systems/ … 08_planning/   (8 modules)

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Quick Start

1. Choose a course based on your background and interest.
2. Start with Module 01 (Systems) and work through sequentially.
3. Use the dashboard for interactive review.
4. Complete the lab for hands-on practice.