AI Models Demystified
Understand what AI models are, how they learn, the major types (LLM, embedding, vision, multimodal, diffusion), and how to choose the right model and provider for any task.
"For this SaaS chatbot, I'd use Claude Haiku with RAG — here's why and what I'd test first"
6 Modules
Each module builds on the previous one. By the end, you have a complete production system.
- 1
What Is a Model?
Mental model of parameters, tokens, and next-token prediction
- 2
How Models Learn
Understanding of training, loss, fine-tuning, and RLHF
- 3
Types of Models
Taxonomy: LLM, embedding, vision, multimodal, diffusion
- 4
The Provider Landscape
Provider comparison across 5 axes
- 5
Choosing the Right Model
Decision framework with evaluation methodology
- 6
Your First Model Decision
Three justified model recommendations for real scenarios
Production patterns you'll master
Synthetic data included
- Tokenizer demos
- Training logs (CSV)
- Model benchmarks
- Provider pricing data
- Real-world scenarios
What you walk away with
Shareable portfolio
A public URL showing your module timeline, patterns mastered, and completion status.
All the code
Download everything as a ZIP — pipelines, guardrails, deployment configs. Yours forever.
Module walkthrough
Each module documented with deliverables and the production pattern you implemented.
Ready to build your ai models demystified?
First course free. $20 per course after that.