LLMOps Evaluation and Responsible Deployment

AT A GLANCE

Is this programme for you?

Built for ai engineers, platform leads, evaluators. AI helps you move faster; every output is checked against references, runnable examples or a human review before you rely on it.

Register interest Ask about mentorship

Who it's for: AI engineers, platform leads, evaluators
IT domain: AI Evaluation LLMOps and Governance (Advanced)
Prerequisites: Generative AI and LLM Applications; Testing and Quality Engineering
How AI is used: Core AI curriculum
Reviewed output: AI evaluation harness and release dashboard
How work is checked: Check against references, runnable examples or domain review; record uncertain outputs
Trainer: Trainer to assign
Status: Planned · dates and fees not yet set

CORE CONCEPTS

10 concepts, each with a practice brief.

Each concept ends in evidence you can show. Briefs are starting points and are reviewed by the trainer before publication.

01
Evaluation datasets and rubrics
Run a controlled example of Evaluation datasets and rubrics for AI evaluation harness and release dashboard; record assumptions, baseline and measured results.
ExperimentAdvancedEvidence: Experiment notebook and comparisonIWA-C33-01
02
Human and automated assessment
Run a controlled example of Human and automated assessment for AI evaluation harness and release dashboard; record assumptions, baseline and measured results.
ExperimentAdvancedEvidence: Experiment notebook and comparisonIWA-C33-02
03
Prompt and model versioning
Run a controlled example of Prompt and model versioning for AI evaluation harness and release dashboard; record assumptions, baseline and measured results.
ExperimentAdvancedEvidence: Experiment notebook and comparisonIWA-C33-03
04
AI application tracing
Run a controlled example of AI application tracing for AI evaluation harness and release dashboard; record assumptions, baseline and measured results.
ExperimentAdvancedEvidence: Experiment notebook and comparisonIWA-C33-04
05
Provider routing and fallback
Run a controlled example of Provider routing and fallback for AI evaluation harness and release dashboard; record assumptions, baseline and measured results.
ExperimentAdvancedEvidence: Experiment notebook and comparisonIWA-C33-05
06
AI cost budgets and usage metering
Run a controlled example of AI cost budgets and usage metering for AI evaluation harness and release dashboard; record assumptions, baseline and measured results.
ExperimentAdvancedEvidence: Experiment notebook and comparisonIWA-C33-06
07
Prompt-injection resilience
Run a controlled example of Prompt-injection resilience for AI evaluation harness and release dashboard; record assumptions, baseline and measured results.
ExperimentAdvancedEvidence: Experiment notebook and comparisonIWA-C33-07
08
Sensitive-data handling in AI workflows
Run a controlled example of Sensitive-data handling in AI workflows for AI evaluation harness and release dashboard; record assumptions, baseline and measured results.
ExperimentAdvancedEvidence: Experiment notebook and comparisonIWA-C33-08
09
AI release regression gates
Run a controlled example of AI release regression gates for AI evaluation harness and release dashboard; record assumptions, baseline and measured results.
ExperimentAdvancedEvidence: Experiment notebook and comparisonIWA-C33-09
10
AI governance and risk records
Run a controlled example of AI governance and risk records for AI evaluation harness and release dashboard; record assumptions, baseline and measured results.
ExperimentAdvancedEvidence: Experiment notebook and comparisonIWA-C33-10