Foundations
LLM cost & latency estimation
Estimate and control token cost, latency and throughput for AI features.
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.
- AIN 401 CO4
Evaluate AI systems with golden sets, calibrated LLM-as-judge, cost/latency metrics and CI regression gates, and justify engineering decisions with evidence.
- MST 502 CO6
Demonstrate Advanced, Autonomous & Mastery competence: complete the Day 76–90 builds, explain the underlying theory, and defend the phase artefact under live questioning.
- MST 505 CO5
Demonstrate Evaluation, Caching, Multimodal & Observability competence: complete the Day 61–75 builds, explain the underlying theory, and defend the phase artefact under live questioning.
- MST 505 CO6
Demonstrate Production, Security, Governance & Mastery competence: complete the Day 76–90 builds, explain the underlying theory, and defend the phase artefact under live questioning.
- MST 506 CO2
Demonstrate Vector Databases & Retrieval Engineering competence: complete the Day 16–30 builds, explain the underlying theory, and defend the phase artefact under live questioning.
- MST 506 CO4
Demonstrate Evaluation, Observability & Retrieval Quality competence: complete the Day 46–60 builds, explain the underlying theory, and defend the phase artefact under live questioning.
- MST 506 CO6
Demonstrate Agentic Retrieval, Scale & Mastery competence: complete the Day 76–90 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.
- MST 508 CO4
Demonstrate Evaluation & Observability competence: complete the Day 46–60 builds, explain the underlying theory, and defend the phase artefact under live questioning.
- MST 508 CO6
Demonstrate Production LLMOps, Security & Mastery competence: complete the Day 76–90 builds, explain the underlying theory, and defend the phase artefact under live questioning.
Taught in weeks & phases
- AIN 401 · Week 2 — How Foundation Models Work: Tokens, Context & Cost
- AIN 401 · Week 12 — LLMOps: Observability, Cost & Latency SLOs, Deployment
- MST 502 · Phase 6 — Advanced, Autonomous & Mastery
- MST 505 · Phase 5 — Evaluation, Caching, Multimodal & Observability
- MST 505 · Phase 6 — Production, Security, Governance & Mastery
- MST 506 · Phase 2 — Vector Databases & Retrieval Engineering
- MST 506 · Phase 4 — Evaluation, Observability & Retrieval Quality
- MST 506 · Phase 6 — Agentic Retrieval, Scale & Mastery
- MST 508 · Phase 1 — Foundations & Theory
- MST 508 · Phase 4 — Evaluation & Observability
- MST 508 · Phase 6 — Production LLMOps, Security & Mastery