Info
Most of this section is AI written.
Foundations
- Machine Learning — Supervised, unsupervised, reinforcement learning
- LLMs — Large language models, transformers, attention
- Embeddings — Vector representations, semantic similarity
- Multimodal AI — Vision, audio, and cross-modal models
LLM Techniques
- Prompt Engineering — Techniques for effective model interaction
- RAG — Retrieval-Augmented Generation
- Fine-tuning — LoRA, QLoRA, and adapting models to domains
- AI Agents — Autonomous systems, tool use, and multi-agent patterns
Infrastructure
- Model Serving — Inference, quantisation, deployment
- Vector Databases — Storage and retrieval for embeddings
- Evaluation & Benchmarking — Measuring model performance
Models & Providers
- Foundation Models — Commercial and open-source LLMs
Safety & Ethics
- AI Safety — Alignment, hallucinations, responsible development
Tools
Agentic Coding
- OpenCode — Can use many providers and models
- Claude Code
- Codex CLI
- Gemini CLI
- Jules
- Devin
- Getting Good Results from Claude Code