MOC

AI Learning Centre

Updated 2 May 2025

moclearningai

Structured learning from fundamentals to advanced topics. This is the place to build understanding — both mine and yours.

Start where you’re curious. Every page stands alone. The connections between ideas are where the real learning happens.

Foundations

The core of how AI learns.

Neural Networks — Where it all starts. From perceptrons to deep learning.
Transformers — The architecture behind everything modern. Attention is all you need.
Embeddings — How meaning gets encoded as numbers. The bridge between language and math.
Training & Fine-Tuning — How models learn from data. Pre-training, fine-tuning, RLHF.

How LLMs Work — The full pipeline from text in to text out. Start here for the big picture.

The art and science of communicating with AI models. System prompts, few-shot learning, chain-of-thought.

Where AI stops being a chatbot and starts being a colleague. Autonomy, tool use, planning, action.

Agent Frameworks — The harnesses: LangChain, CrewAI, LangGraph, MCP, native APIs. How to build agents in practice.

Retrieval-Augmented Generation — grounding AI in external knowledge. The most common real-world AI application pattern.

The ecosystem — libraries, platforms, and developer tools. See also AI Software & Tools for the complete software section.

You want to…	Follow this path
Understand AI from scratch	Neural Networks → Transformers → How LLMs Work → Training & Fine-Tuning
Build with AI	Prompt Engineering → RAG & Retrieval → AI Agents → Agent Frameworks
Understand the risks	AI Safety Courses → AI Security → AI Alignment
Know the models	AI Models → AI Companies → How LLMs Work
Go deep on theory	Embeddings → Transformers → Attention Is All You Need → Scaling Laws for Neural Language Models