ALY 4520 — MLOps: Operationalizing AI
3 semester hoursUndergraduateLectureusually offered: springOnlineOnline
Examines the machine learning operations, or MLOps, life cycle for designing, deploying, and managing scalable machine learning systems. Surveys emerging trends, such as serverless computing and edge deployments, to illuminate future directions in MLOps. Highlights foundational methods for data ingestion, pipeline orchestration, and performance monitoring while addressing ethical and security considerations. Emphasizes cross-functional collaboration between data science and engineering for production-ready solutions that prioritize reliability and reproducibility. Demonstrates how automation strategies and best practices accelerate feedback loops and streamline model updates. Encourages a practice-based approach that integrates experimental results with continuous delivery to align with organizational goals.
Prerequisites
- ALY 4020 (min B)
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Spring 2026 | 1 | 4 | 30 | 13% | 26.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 0% · T 0% · W 0% · Th 0% · F 0%
Common patterns: async (100% of sections) — in patterns, R means Thursday
Professors
Spring
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (ALY course descriptions) · All ALY courses · Plan it at numap.app