Course Catalog

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Complete catalog of all courses managed by the Active Inference Institute publishing pipeline. Every course listed here has a corresponding entry in COURSE_REGISTRY.

Course Categories

Category	Courses	Description
Core	1 consolidated + 4 legacy individual	The primary Active Inference textbook
Level-Adapted	6	Same curriculum adapted for different audiences
Domain-Specific	7	Active Inference applied to specific fields
Supplementary	1	Skills tracks that support the courses
Archive	1	38 playlists / ~821 YouTube video transcripts

Core (Consolidated)

`active-inference` — Active Inference (Core)

The primary consolidated course combining all four units of the Active Inference textbook. This is the recommended course for full rendering.

Field	Value
Registry ID	`active-inference`
Display name	Active Inference (Core)
Path	`course_development/active_inference/`
Structure	4 units x 8 modules = 32 modules
Content files	`module.md`, `questions.md`, `practice_quiz.md`, `lab.md`
Static dirs	`04_computer_science/src/active_inference`, `04_computer_science/tests`, `resources`

Units

Unit	Directory	Topic	Modules
1	`01_philosophy/`	Philosophy of Active Inference	8
2	`02_cognitive_science/`	Cognitive Science of Active Inference	8
3	`03_math/`	Mathematics of Active Inference	8
4	`04_computer_science/`	Computer Science of Active Inference	8

Module Topics (per unit)

#	Philosophy	Cognitive Science	Mathematics	Computer Science
1	Systems	Systems	Systems	Systems
2	Agents	Agents	Agents	Agents
3	Perception	Perception	Perception	Perception
4	Cognition	Cognition	Cognition	Cognition
5	Action	Action	Action	Action
6	Learning	Learning	Learning	Learning
7	Communication	Communication	Communication	Communication
8	Planning	Planning	Planning	Planning

Each module covers the same topic from a different disciplinary perspective, enabling cross-course comparison.

Cross-Course Navigation

Modules link to their counterparts via README files:

| [Philosophy](../../01_philosophy/01_systems/) | Boundaries, Markov Blankets |
| [Cognitive Science](../../02_cognitive_science/01_systems/) | Neural Assemblies |
| [Mathematics](../../03_math/01_systems/) | Matrices, Probability |
| [Computer Science](../../04_computer_science/01_systems/) | Generative Models |

Shared Resources

Resource	Path	Description
Notation Table	`resources/notation_table.md`	Symbol definitions used across all units
Glossary	`resources/glossary.md`	Term definitions
References	`resources/references.md`	Bibliographic citations

# Render the full consolidated core course
uv run python scripts/generate_all_outputs.py --course active-inference --formats txt,md

Legacy Individual Courses (Deprecated)

These entries allow rendering individual units separately. They are deprecated in favor of active-inference:

ID	Unit	Path
`ai-philosophy`	Philosophy	`course_development/active_inference/01_philosophy`
`ai-cognitive-science`	Cognitive Science	`course_development/active_inference/02_cognitive_science`
`ai-math`	Mathematics	`course_development/active_inference/03_math`
`ai-computer-science`	Computer Science	`course_development/active_inference/04_computer_science`

# Render only the philosophy unit
uv run python scripts/generate_all_outputs.py --course ai-philosophy --formats txt,md

Level-Adapted Courses

These courses adapt the Active Inference curriculum for different educational levels and audiences. Each uses the same 4-unit x 8-module structure with content tailored for its audience.

ID	Display Name	Audience	Path
`ai-es`	Elementary School	Ages 6-10	`course_development/active_inference_es/`
`ai-family`	Family	Multi-generational, ages 5+	`course_development/active_inference_family/`
`ai-ms`	Middle School	Ages 11-13	`course_development/active_inference_ms/`
`ai-hs`	High School	Ages 14-18	`course_development/active_inference_hs/`
`ai-101`	College Introductory	Undergraduate	`course_development/active_inference_101/`
`ai-401`	Advanced PhD Seminar	Graduate/PhD	`course_development/active_inference_401/`

Common Structure

All level-adapted courses share:

Unit/module glob: [0-9][0-9]_* at both unit and module level
Content files: module.md, questions.md, practice_quiz.md, lab.md
Syllabus: syllabus.md per unit

Audience Differences

Level	Language	Depth	Lab Style
Elementary	Simple, concrete metaphors	Introductory concepts	Hands-on activities
Family	Accessible, multi-age	Shared exploration	Group activities
Middle School	Age-appropriate academic	Foundational	Guided experiments
High School	Academic with scaffolding	Intermediate	Structured labs
College 101	University-level prose	Standard textbook depth	Research-oriented
Advanced 401	Graduate-level academic	Full mathematical rigor	Research proposals

# Render all level-adapted courses
for course in ai-es ai-family ai-ms ai-hs ai-101 ai-401; do
  uv run python scripts/generate_all_outputs.py --course $course --formats txt,md
done

Domain-Specific Courses

These courses apply Active Inference to specific professional and research domains.

ID	Display Name	Focus Area	Path
`ai-embodied`	Embodied Active Inference	Robotics, morphological computation, sensorimotor coupling	`course_development/domains/active_inference_embodied/`
`ai-organizations`	Organizations	Management, governance, collective intelligence	`course_development/domains/active_inference_organizations/`
`ai-robotics`	Robotics Applications	Practical robotics implementations	`course_development/domains/active_inference_robotics/`
`ai-crochet`	Active Inference & Crochet	Fiber arts, stitch patterns, morphological computation through craft	`course_development/domains/active_inference_crochet/`
`ai-inventions`	Active Inference & Inventions	Creative engineering, design thinking, innovation processes	`course_development/domains/active_inference_inventions/`
`ai-metallurgy`	Active Inference & Metallurgy	Materials science, alloy design, phase transformations	`course_development/domains/active_inference_metallurgy/`
`ai-comedy`	Active Inference & Comedy	Comedic structure, timing dynamics, crowd reading, improvisation	`course_development/domains/active_inference_comedy/`

Structure

Same 4-unit x 8-module pattern, adapted for domain context:

Unit/module glob: [0-9][0-9]_*
Content files: module.md, questions.md, practice_quiz.md, lab.md
Syllabus: syllabus.md

# Render a domain course
uv run python scripts/generate_all_outputs.py --course ai-embodied --formats txt,md

GNN Syntax Track

`gnn` — GNN Syntax Track

A supplementary skills track that teaches Generalized Notation Notation (GNN) using five verbatim exemplars from the GNN v5.0.3 exemplar corpus. This is not one of the 14 spiral courses and is not counted in the 464-module total.

Field	Value
Registry ID	`gnn`
Display name	GNN Syntax Track
Path	`course_development/gnn/`
Structure	1 lesson module (`01_gnn_syntax/`) + 5 exemplar models
Module glob	`[0-9][0-9]_*`
Content files	`module.md`, `questions.md`, `practice_quiz.md`, `lab.md`
Syllabus	`README.md` (track overview)
Source pin	GNN v5.0.3, commit `8f293d9ba810e6eda5c09842d9c7ed9ffa5f92c1`

The lesson walks through the Static Perception Model section by section, computes its perception update, and runs the GNN pipeline over the shipped exemplars. See course_development/gnn/README.md for the level mapping and provenance.

# Render the track
uv run python scripts/generate_all_outputs.py --course gnn --formats txt,md

YouTube Transcript Archive

`youtube` — YouTube Transcripts

An archive of transcripts from the Active Inference Institute YouTube channel (38 playlists, ~821 videos per playlist metadata).

Field	Value
Registry ID	`youtube`
Display name	YouTube Transcripts
Path	`course_development/youtube/`
Unit glob	`*` (playlist directories)
Module glob	`[0-9][0-9]_*` (video directories within playlists)
Content files	`module.md` only

YouTube Pipeline

The YouTube archive has a dedicated multi-stage pipeline:

Enumerate playlists from the channel
Scaffold course directory structures per playlist
Transcribe videos (auto-captions, then Whisper fallback)
Render through the standard batch processing pipeline

# List playlists
uv run python scripts/render_youtube_courses.py --list-playlists

# Scaffold and render a single playlist
uv run python scripts/render_youtube_courses.py --course active-inference-textbook-group --formats txt,md

# Full archive render
uv run python scripts/render_youtube_courses.py --formats txt,md

See YOUTUBE.md for the full YouTube processing guide.

Module File Reference

Every Active Inference module (across all course types) contains:

File	Purpose	Rendering Category	Output Formats
`module.md`	Main lecture content	`lecture-content/`	PDF, HTML, DOCX, TXT, MD, MP3
`questions.md`	20 study questions	`study-guides/`	PDF, HTML, DOCX, TXT, MD, MP3
`practice_quiz.md`	7 MC + 3 FR quiz	`study-guides/`	PDF, HTML, DOCX, TXT, MD, MP3
`lab.md`	Lab protocol/activity	`lab-protocols/`	PDF, HTML, DOCX, TXT, MD, MP3
`dashboard.html`	Interactive dashboard	(copied as-is)	HTML
`README.md`	Module overview & navigation	(not rendered)	--
`AGENTS.md`	Agent/contributor guidelines	(not rendered)	--

Dashboard Features

Each dashboard.html is a standalone interactive page with:

Concept cards with expandable detail sections
Self-assessment quiz with scoring
Study checklist with progress tracking
Module navigation links
Dark theme UI

Course Registry Configuration

All courses are registered in COURSE_REGISTRY inside software/src/batch_processing/config.py. Key fields:

Field	Type	Description
`rel_path`	`str`	Path from repo root to course directory
`display_name`	`str`	Human-readable name for logs/CLI
`module_glob`	`str`	Glob pattern for module directories
`unit_glob`	`str`	Glob pattern for unit directories (multi-level courses)
`content_files`	`list[str]`	Files to render per module
`syllabus_location`	`str`	Where to find the syllabus
`static_dirs`	`list[str]`	Additional directories to copy during publish

Adding a New Course

Add an entry to COURSE_REGISTRY in software/src/batch_processing/config.py
Create the directory structure under course_development/
Add the course to publish.toml at the repo root
Run: uv run python scripts/generate_all_outputs.py --course YOUR_ID --dry-run

Quick Commands

# List all registered course IDs
uv run python -c "from src.batch_processing.config import COURSE_REGISTRY; print('\n'.join(COURSE_REGISTRY.keys()))"

# Count modules for a course
uv run python -c "
from pathlib import Path
from src.batch_processing.utils import find_modules_for_course
from src.batch_processing.config import COURSE_REGISTRY
reg = COURSE_REGISTRY['active-inference']
modules = find_modules_for_course(Path(reg['rel_path']), 'active-inference')
print(f'{len(modules)} modules')
"

# Dry-run preview for all enabled courses
python publish.py --dry-run

Last Updated: 2026-08-02

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COURSE_CATALOG.md

COURSE_CATALOG.md

Course Catalog

Course Categories

Core (Consolidated)

`active-inference` — Active Inference (Core)

Units

Module Topics (per unit)

Cross-Course Navigation

Shared Resources

Legacy Individual Courses (Deprecated)

Level-Adapted Courses

Common Structure

Audience Differences

Domain-Specific Courses

Structure

GNN Syntax Track

`gnn` — GNN Syntax Track

YouTube Transcript Archive

`youtube` — YouTube Transcripts

YouTube Pipeline

Module File Reference

Dashboard Features

Course Registry Configuration

Adding a New Course

Quick Commands

FilesExpand file tree

COURSE_CATALOG.md

Latest commit

History

COURSE_CATALOG.md

File metadata and controls

Course Catalog

Course Categories

Core (Consolidated)

active-inference — Active Inference (Core)

Units

Module Topics (per unit)

Cross-Course Navigation

Shared Resources

Legacy Individual Courses (Deprecated)

Level-Adapted Courses

Common Structure

Audience Differences

Domain-Specific Courses

Structure

GNN Syntax Track

gnn — GNN Syntax Track

YouTube Transcript Archive

youtube — YouTube Transcripts

YouTube Pipeline

Module File Reference

Dashboard Features

Course Registry Configuration

Adding a New Course

Quick Commands

`active-inference` — Active Inference (Core)

`gnn` — GNN Syntax Track

`youtube` — YouTube Transcripts