Arcadia AI — Master's Program
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Program  /  Semester 3 — Specialization & Research
Practicum

Practicum 3: Team Industrial Project with SLA and Quality Constraints

A team industrial project: production ML with real SLA, latency, and quality constraints

Instructor to be announced

About the course

The third-semester practicum is the program's flagship engineering project. Teams of 3-4 work on a challenge from an industry partner or a real open-source project with production-level requirements: SLA, latency budget, and monitored quality. Students apply skills from every previous course under real-world constraints. The outcome is a delivered service complete with an SLO report, a postmortem, and a public demo.

What you'll learn

Deliver a team ML project with explicit SLOs and documented tradeoff decisions
Run load testing and optimize a system to meet a latency budget
Write a production postmortem with quantitative root-cause analysis

Key topics

Requirements decomposition and ML system design under constraints
Architectural decisions: latency vs. accuracy tradeoffs
Agile process in an ML team: sprints, Definition of Done for ML
Load testing and capacity planning
SLA/SLO/SLI: design and measurement
Production postmortem and root-cause analysis (RCA)
Demo and technical presentation for a non-technical audience
This description was generated automatically and has not yet been reviewed by an instructor — it's a draft for discussion.