How to Find Specific Modules or Lessons in AI For Beginners: A Complete Navigation Guide

Quick answer: Browse the master lesson table in the root README.md, use the two-digit numeric prefixes in folder names, or grep for keywords across the lessons/ directory to locate any module instantly.

The AI For Beginners repository by Microsoft organizes a comprehensive 12-week curriculum under a strict naming convention. This guide shows you how to navigate the lessons/ directory structure efficiently, whether you prefer browsing, searching, or programmatic discovery.

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Understanding the Repository Structure

All course content lives in the top-level lessons/ directory. Each major topic is a numbered folder following the pattern {number}-{TopicName}:

Folder	Topic
0-course-setup	Environment setup
1-Intro	Introduction to AI
2-Symbolic	Symbolic AI
3-NeuralNetworks	Neural Networks fundamentals
4-ComputerVision	Computer Vision
5-NLP	Natural Language Processing
6-Other	Other AI Techniques
7-Ethics	AI Ethics
X-Extras	Supplementary material

Inside each folder, you'll find consistent components:

• README.md — Overview and navigation index for that topic
• Sub-lesson folders — Named with two-digit prefixes (e.g., 07-ConvNets/, 18-Transformers/)
• Jupyter notebooks — Separate .ipynb files for PyTorch and TensorFlow implementations
• lab/ — Hands-on assignments with their own README.md and notebooks
• Supporting files — assignment.md, requirements-*.txt, and visual sketchnotes

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Method 1: Use the Master Lesson Table

The fastest way to locate any lesson is the central lesson index in the root README.md. Open the repository's main page and scroll to the "Content" section.

The table maps numeric IDs to human-readable titles with direct links to each lesson's README.md or notebook. Search this table for your keyword and click through.

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Method 2: Navigate by Numeric Prefix

Each lesson folder uses a two-digit prefix system that enables direct navigation without browsing:

# Computer Vision → Convolutional Neural Networks

lessons/4-ComputerVision/07-ConvNets/

# NLP → Transformers

lessons/5-NLP/18-Transformers/

Knowing the prefix lets you construct the path directly. For example, the ConvNets PyTorch notebook resides at:

lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb

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Method 3: Search by Keyword with Grep

For command-line users, grep across the lessons/ hierarchy finds any lesson by content:

# Find lessons mentioning "Transformer"

grep -R --line-number "Transformer" lessons/*/README.md

Sample output:

lessons/5-NLP/18-Transformers/README.md:1: # Transformers. BERT.

lessons/5-NLP/18-Transformers/README.md:12: https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb

This works because every lesson title appears in its README.md first line.

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Method 4: Leverage Sketchnotes for Thematic Discovery

Each major topic includes a visual one-pager in lessons/sketchnotes/. These diagrams help you identify the correct thematic block before drilling into specific files.

Browse the sketchnotes folder to orient yourself, then navigate to the corresponding numbered folder.

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Programmatic Lesson Discovery

List All Lessons with Python

import pathlib
import re

root = pathlib.Path("lessons")
title_pattern = re.compile(r"#\s+(.*)")

def list_lessons():
    for md in root.rglob("README.md"):
        with md.open(encoding="utf-8") as f:
            first_line = f.readline()
            m = title_pattern.match(first_line)
            if m:
                title = m.group(1).strip()
                rel_path = md.relative_to(root)
                print(f"{rel_path.parent}/{rel_path.name}: {title}")

if __name__ == "__main__":
    list_lessons()

Excerpt output:

0-course-setup/setup.md: Course Setup
1-Intro/README.md: Introduction to AI
2-Symbolic/README.md: Symbolic AI
3-NeuralNetworks/README.md: Neural Networks
4-ComputerVision/README.md: Computer Vision
5-NLP/README.md: Natural Language Processing
6-Other/README.md: Other AI Techniques
7-Ethics/README.md: AI Ethics
X-Extras/X1-MultiModal/README.md: Multi‑Modal Networks, CLIP and VQGAN

Open Notebooks Programmatically in Jupyter

from IPython.display import IFrame

def show_notebook(path):
    """Render a notebook in the current Jupyter cell."""
    return IFrame(src=path, width="100%", height="800px")

# Example: open the PyTorch ConvNet notebook

show_notebook("lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb")

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Key Index Files Reference

File	Purpose	Direct Link
README.md (root)	Master lesson table and navigation hub	Root README
lessons/4-ComputerVision/README.md	All CV sub-lessons (CNNs, GANs, Transfer Learning)	CV Index
lessons/5-NLP/README.md	All NLP sub-lessons (Embeddings, Transformers, NER)	NLP Index
lessons/sketchnotes/	Visual topic overviews	Sketchnotes

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Summary

• Master lesson table in root README.md provides clickable links to every lesson
• Two-digit numeric prefixes enable direct folder navigation (e.g., 07-ConvNets, 18-Transformers)
• grep searches across lessons/ find content by keyword in README.md files
• Sketchnotes offer visual thematic orientation before file-level browsing
• Consistent naming means every topic follows lessons/{number}-{Topic}/{number}-{Lesson}/ structure

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Frequently Asked Questions

Where is the complete list of all lessons in AI For Beginners?

The complete list lives in the "Content" section of the root README.md. This master table contains every lesson ID, title, and direct link to its markdown page or notebook. It is the single source of truth for curriculum navigation according to the repository's source code.

How do I find the notebook for a specific topic like Transformers?

Use the numeric prefix system: Transformers are lesson 18 in the NLP section (5-NLP), so navigate to lessons/5-NLP/18-Transformers/. You'll find TransformersPyTorch.ipynb and TransformersTensorFlow.ipynb inside. The topic's README.md also lists all available notebooks and their purposes.

Can I search lessons without cloning the repository?

Yes. Use GitHub's search bar with the repo: qualifier: repo:microsoft/AI-For-Beginners "your keyword". Alternatively, browse the root README's lesson table on the web interface, or use the sketchnotes folder to visually identify your target topic before following links.

What do the sketchnotes contain and how do they help?

The sketchnotes are one-page visual summaries for each major topic (Intro, Neural Networks, Computer Vision, NLP, etc.). They diagram key concepts and the lesson flow within that topic. Use them to quickly identify which numbered folder contains the material you need before diving into specific files.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}