LLM Fundamentals for Data Professionals
How large language models actually work, explained for people who think in tables.
Prompt Engineering
Writing instructions an AI can't misread.
Retrieval-Augmented Generation (RAG)
Giving an LLM a library card instead of asking it to memorize everything.
AI Agents & Agentic Workflows
Systems that plan, act, and check their own work.
Fine-Tuning vs. Prompting
Choosing whether to retrain the model or just talk to it better.
LLMOps
Running language models in production without losing control of them.
Multimodal AI
Models that read, see, and listen at once.
Small Language Models & On-Device AI
When smaller and local beats bigger and cloud-hosted.
AI Copilots for Analytics
Assistants that draft the query, the chart, and the first-pass insight.
Evaluating & Reducing Hallucination
Building guardrails for a system that will confidently make things up.
Building Internal AI Tools
Turning these ideas into something your own team actually uses.