AI Models Demystified

3 Interactive Sessions

Short, interactive sessions: watch it work, try it, then build it yourself. You can go deeper at any time in the written chapters.

1. 1

   How an AI model works, and how it learned

   It guesses the next word, and it learned to guess well by reading.

2. 2

   Different jobs need different models

   Different jobs need different kinds of model, and each kind comes in versions that trade off against each other.

3. 3

   Choose the right model, and show why

   Name the task and its hard limits, make a shortlist, pick one and give your reason. Then watch your pick run.

How this certificate is scored

Your certificate shows how many of your written answers met the rubric below, checked by an AI grader. Anyone who checks your certificate sees it.

• You answer 6 short questions, one for each module, in your own words (at least 40 words each).
• An AI grader checks each answer against what its module asks for: it must answer the question, use the course's practice case specifically, and be correct.
• To pass, at least 5 of the 6 answers must meet that bar. The certificate says the answers were graded by AI.

The rubric

1. Module 1, What Is a Model?: Mental model of parameters, tokens, and next-token prediction.
2. Module 2, How Models Learn: Understanding of training, loss, fine-tuning, and RLHF.
3. Module 3, Types of Models: Taxonomy: LLM, embedding, vision, multimodal, diffusion.
4. Module 4, The Provider Landscape: Provider comparison across 5 axes.
5. Module 5, Choosing the Right Model: Decision framework with evaluation methodology.
6. Module 6, Your First Model Decision: Three justified model recommendations for real scenarios.

What you walk away with