AI Operations (AIOps) Practitioner Track

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AI Operations (AIOps) Practitioner Track is a self-paced online course: 6 modules and 18 lessons that you work through on your own schedule.

Orientation: The Operating Model for Model-Backed Systems

Lessons

What Changes When a Nondeterministic Component Enters Production Defining the Unit of Work and Its Service Level Objectives Ownership, Interfaces and the Change Surface

Evaluation Sets and Failure Taxonomy

Lessons

Building the Evaluation Set That Everything Else Depends On A Failure Taxonomy, and Why the Fix Differs Per Bucket Graders: Automated Scoring You Can Trust

Context: Retrieval Quality and Context Budgets

Lessons

Measuring Retrieval Quality Independently of Generation Context Budgets and What to Spend Them On Prompt and Instruction Management as Configuration Discipline

Cost and Reliability Engineering

Lessons

Routing by Difficulty: The Primary Cost Lever Caching, Batching and Request Shaping Structured Output, Validation, Refusal and Escalation

Autonomy as a Security Surface

Lessons

Agent Autonomy Treated as a Security Surface Audit Logging for Agent Actions The Kill Path, and Testing That It Works

Observability, Incidents and Staged Rollout

Lessons

Observability and the Regression Ritual Incident Response When Behavior Changes Underneath You Staged Rollout, Named Ownership and Steady-State Operation
About this courseThis is a self-paced educational course. Completing it does not award a professional certification, license, degree or academic credit, and it does not count toward any licensing or continuing-education requirement. Exam-prep courses are independent study material: we are not affiliated with or endorsed by the exam provider, no exam voucher is included, and a certification is only awarded by the provider after you pass its exam. It makes no promise of employment, pay or exam results.
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