Foundations
Foundation model mechanics
Explain tokenization, context windows, sampling and characteristic failure modes of LLMs.
Target proficiency: Applied
Course outcomes
- AIN 401 CO1
Explain foundation-model behaviour — tokenization, context windows, sampling, cost — and characteristic failure modes such as confabulation and prompt injection.
- AI 101 CO3
Describe how neural networks, perception systems and large language models work and analyse their typical failure modes.
- MST 502 CO1
Demonstrate Foundations & Theory competence: complete the Day 1–15 builds, explain the underlying theory, and defend the phase artefact under live questioning.
- MST 505 CO1
Demonstrate Foundations & Theory competence: complete the Day 1–15 builds, explain the underlying theory, and defend the phase artefact under live questioning.
- MST 507 CO2
Demonstrate LLMs, Prompting & the Agentic Loop competence: complete the Day 16–30 builds, explain the underlying theory, and defend the phase artefact under live questioning.
- MST 508 CO1
Demonstrate Foundations & Theory competence: complete the Day 1–15 builds, explain the underlying theory, and defend the phase artefact under live questioning.