Learn AI from fundamentals to mastery through interactive, executable chapters.
Every chapter is generated by Berta AI. Every chapter is free, open-source, and yours to fork, clone, and modify.
This repository contains TWO types of chapters:
A structured, comprehensive learning journey from Python basics to advanced AI specializations.
Start here if you're new to AI or want a guided progression.
Special chapters created on-demand based on what you need to learn.
Request a chapter on any AI topic, and Berta will generate it for you.
graph LR
A["📚 Foundation<br/>Chapters 1-5"] --> B["💼 Practitioner<br/>Chapters 6-15"]
B --> C["🚀 Advanced<br/>Chapters 16-25+"]
D["💬 User Request"] --> E["🤖 Berta Generates"]
E --> F["📦 New Chapter<br/>Added"]
style A fill:#e1f5ff
style B fill:#f3e5f5
style C fill:#e8f5e9
style D fill:#fff3e0
style F fill:#fce4ec
Learn essential skills for AI: Python, data structures, math, and computational thinking.
| Chapter | Topic | Time | Status |
|---|---|---|---|
| 1 | Python Fundamentals for AI | 8h | ✅ Available |
| 2 | Data Structures & Algorithms | 6h | ✅ Available |
| 3 | Linear Algebra & Calculus | 10h | ✅ Available |
| 4 | Probability & Statistics | 8h | ✅ Available |
| 5 | Software Design & Best Practices | 6h | ✅ Available |
Apply what you've learned to real-world machine learning and AI problems.
| Chapter | Topic | Time | Status |
|---|---|---|---|
| 6 | Introduction to Machine Learning | 8h | ✅ Available |
| 7 | Supervised Learning: Regression & Classification | 10h | ✅ Available |
| 8 | Unsupervised Learning: Clustering & Dimensionality Reduction | 8h | ✅ Available |
| 9 | Deep Learning Fundamentals | 12h | ✅ Available |
| 10 | Natural Language Processing Basics | 8–10h | ✅ Available |
| 11 | Large Language Models & Transformers | 10h | ✅ Available |
| 12 | Prompt Engineering & In-Context Learning | 6h | ✅ Available |
| 13 | Retrieval-Augmented Generation (RAG) | 8h | ✅ Available |
| 14 | Fine-tuning & Adaptation Techniques | 8h | ✅ Available |
| 15 | MLOps & Model Deployment | 8h | ✅ Available |
Dive deep into cutting-edge techniques and specialized domains.
| Chapter | Topic | Time | Status |
|---|---|---|---|
| 16 | Multi-Agent Systems Architecture | 10h | ✅ Available |
| 17 | Advanced RAG & Knowledge Systems | 10h | ✅ Available |
| 18 | Reinforcement Learning Fundamentals | 12h | ✅ Available |
| 19 | Model Optimization & Inference | 8h | ✅ Available |
| 20 | Building Production AI Systems | 10h | ✅ Available |
| 21 | AI for Finance (Specialized) | 10h | ✅ Available |
| 22 | AI Safety & Alignment | 8h | ✅ Available |
| 23 | Building Your Own AI Products | 8h | ✅ Available |
| 24 | Research & Cutting-Edge Techniques | 8h | ✅ Available |
| 25 | AI Governance & Ethics | 6h | ✅ Available |
Choose your journey. Each path combines chapters in a specific sequence based on your goals.
Comprehensive progression covering all major AI domains.
- Chapters: 1 → 2 → 3 → 4 → 5 → 6 → 9 → 11 → 13 → 15 → 20
- Total Time: ~110 hours
- Skills: Full-stack AI engineering, systems thinking, deployment
- Best For: Building diverse AI applications
Deep dive into machine learning theory and practice.
- Chapters: 1 → 2 → 3 → 4 → 6 → 7 → 8 → 9 → 15 → 19 → 20
- Total Time: ~100 hours
- Skills: Advanced ML, model optimization, production systems
- Best For: Machine learning engineers and researchers
Specialized focus on language models and NLP.
- Chapters: 1 → 5 → 10 → 11 → 12 → 13 → 14 → 17 → 20 → 23
- Total Time: ~90 hours
- Skills: LLM expertise, prompt engineering, RAG systems
- Best For: NLP specialists, LLM application builders
Finance-specific AI techniques (designed with trading/treasury expertise).
- Chapters: 1 → 3 → 4 → 6 → 7 → 21 → 19 → 20 → 23
- Total Time: ~85 hours
- Skills: Financial modeling, time series, risk, trading systems
- Best For: Finance professionals, fintech engineers
Accelerated introduction to core AI concepts.
- Chapters: 1 → 5 → 6 → 9 → 11 → 23
- Total Time: ~48 hours
- Skills: Core AI concepts, ability to build simple apps
- Best For: Quick learners, career changers
Get started in 5 minutes:
git clone https://github.com/luigipascal/berta-chapters.git
cd berta-chapterspip install -r requirements.txtpython interactive/berta.pyThis gives you an interactive experience with:
- Learning path selector — find the right path for your goals
- Skill assessment — discover where to start based on your experience
- Progress tracker — track chapters completed and hours invested
- Knowledge quizzes — test yourself with AI-related questions
- Chapter navigator — explore every chapter in detail
cd chapters/chapter-01-python-fundamentals
jupyter notebook notebooks/01_introduction.ipynbpython templates/chapter_template.py -n 2 -t "Data Structures & Algorithms" --hours 6Have a specific AI topic you want to learn? Ask Berta to create it.
👉 Open a Chapter Request Issue
Tell us:
- What topic you want to learn
- Your experience level
- Why you need it
- Any specific focus areas
Berta will generate a complete, executable chapter and respond with the link. No paywall. No signup. Free forever.
graph LR
A["You Request<br/>a Topic"] --> B["Berta AI<br/>Generates"]
B --> C["Chapter<br/>Repository<br/>Created"]
C --> D["You Learn<br/>& Contribute"]
style A fill:#fff3e0
style B fill:#e3f2fd
style C fill:#f3e5f5
style D fill:#e8f5e9
- 🎓 Structured Learning: Follow proven learning paths or create your own
- 💻 Learn by Doing: Every chapter has executable code, notebooks, and exercises
- 🔓 100% Open: Free, open-source, no paywalls, no tracking
- 🤖 AI-Generated: Transparently created by Berta AI for consistency and scale
- 📦 GitHub Native: Clone, fork, contribute—all on GitHub
- 🌍 Community-Driven: Request chapters you need; community shapes the curriculum
- ⚡ Always Fresh: Chapters improve over time based on feedback
Every Berta chapter includes:
- README.md — Learning objectives, prerequisites, time estimate
- Jupyter Notebooks — Three progressive difficulty levels (intro → intermediate → advanced)
- Production Scripts — Real-world Python code you can use and learn from
- Exercises — Hands-on problems with solutions
- Diagrams & Visualizations — Mermaid diagrams explaining concepts
- Datasets — Sample data for practice
- requirements.txt — All dependencies
chapters/chapter-XX-topic/
├── README.md
├── notebooks/
│ ├── 01_introduction.ipynb ← Start here
│ ├── 02_intermediate.ipynb
│ └── 03_advanced.ipynb
├── scripts/
│ ├── main_application.py
│ └── utilities.py
├── exercises/
│ ├── exercises.py
│ └── solutions/
├── assets/diagrams/
├── datasets/
└── requirements.txt
First time here?
→ Run python interactive/berta.py for the interactive experience
→ Read GETTING_STARTED.md
Want a visual overview?
→ Read SYLLABUS.md
Want to understand the full curriculum?
→ Read CURRICULUM.md
Want to request a custom chapter?
→ Read CHAPTER_REQUEST_GUIDE.md
Want to contribute improvements?
→ Read CONTRIBUTING.md
Want to know what's coming?
→ Read ROADMAP.md
Want to generate a new chapter?
→ Run python templates/chapter_template.py -n <number> -t "<title>"
pie title Curriculum Breakdown
"Foundation (1-5)" : 5
"Practitioner (6-15)" : 10
"Advanced (16-25)" : 10
"Community Requested" : 999
- Chapters Available Now: 25 (216 hours of content) — all tracks complete
- Total Planned Chapters: 25+
- Jupyter Notebooks: 75 interactive notebooks
- SVG/Mermaid Diagrams: 67 professional diagrams
- Exercises: 100+ problems with solutions
- Datasets: 30+ practice datasets
- Community-Requested Chapters: Growing daily
- Found an issue? → Open an issue
- Want to improve a chapter? → Submit a PR
- Have a suggestion? → Start a discussion
- Want to request a chapter? → Request here
Berta AI is the generative engine behind every chapter in this curriculum.
- ✅ Ensures consistency across all chapters
- ✅ Generates pedagogically sound, practical content
- ✅ Improves over time based on community feedback
- ✅ Works 24/7 to fulfill chapter requests
- ✅ Transparent about the generation process
Visit berta.one for more about Berta AI.
Every chapter is marked with "Generated by Berta AI" so you know exactly where the content comes from.
Luigi Pascal Rondanini is an author, publisher, and Treasury Systems Consultant with 35+ years of experience in financial systems and AI/ML transformation.
- 🏦 Former FX trading floor professional (London, Milan, Basel, Riyadh)
- 🔧 Expert in treasury systems, transformation, and organizational AI
- 📚 Founder of Rondanini Publishing Ltd (20+ digital properties)
- 🎙️ Host of Unseen Author Journeys podcast
- 🎵 Composer, audiobook narrator, multimedia creator
- ✍️ Author on Medium and Goodreads
Luigi designed the Berta Chapters curriculum to answer the question: "How can we make AI education truly accessible, practical, and community-driven?"
All content in Berta Chapters is released under the MIT License.
You're free to:
- ✅ Use chapters for learning
- ✅ Copy and modify content
- ✅ Create derivative works
- ✅ Use in commercial projects
Just include attribution to Berta AI and Luigi Pascal Rondanini.
- Berta AI (Official Site): https://berta.one
- LLM Cost Optimizer: https://llm.berta.one
- Berta Chapters (GitHub): https://github.com/luigipascal/berta-chapters
- Personal Site: https://rondanini.net
- LinkedIn: https://uk.linkedin.com/in/rondanini
- Medium: https://medium.com/@info_38412
- Goodreads: https://www.goodreads.com/author/show/43665358.Luigi_Pascal_Rondanini
- Publisher Site: https://www.rondanini.com
- Rondanini Publishing on Medium: https://medium.com/rondanini-publishing
- All Sites Directory: https://sites.rondanini.net
Love Berta Chapters? Help others discover it!
- ⭐ Star this repo on GitHub
- 🔗 Share the link with friends and colleagues
- 💬 Post about it on social media
- 📧 Recommend it in communities you're part of
- 🤝 Contribute improvements and new chapters
Every share helps more people learn AI. Thank you! 🙏
Created by Luigi Pascal Rondanini | Generated by Berta AI
Last Updated: May 2026
All chapters maintained and continuously improved based on community feedback.