Course Objective & Scope
Many models that succeed in a pilot fail to scale in production; without versioning, monitoring, evals and cost control, reliability drops quickly. This course helps non-coding managers understand MLOps and LLMOps practices, ask their teams the right questions and assess platform investments with confidence.
The operational differences between classic ML and LLM applications, including prompt and model versioning, observability, tracing, guardrails and token cost, are explained in business language with live demos. Participants produce an MLOps/LLMOps maturity assessment and an investment priority list for their organisation.
Who Should Attend?
- IT, data and analytics directors
- Product and platform managers responsible for AI products
- Team leads managing engineering teams
- Managers responsible for operational risk and IT governance
Key Takeaways
- Explain the stages and critical control points of the ML and LLM lifecycle
- Define indicators to monitor for model performance, drift, hallucination and cost
- Assess MLOps maturity and rank investment priorities
- Choose consciously between managed cloud platforms and open-source tooling
- Define responsibilities between the platform team and product teams
Curriculum
From Pilot to Production: Why MLOps?
- Common reasons models fail in production
- MLOps and LLMOps concepts and their relation to DevOps
The Classic ML Lifecycle
- Data and model versioning, experiment tracking, model registry
- CI/CD, automated retraining and drift monitoring
Operations Specific to LLM Applications
- Prompt and model versioning, eval sets, LLM-as-a-judge
- Observability, tracing and guardrail layers
- Token cost, latency and capacity management
Platform and Tooling Options
- MLflow, Kubeflow and open-source stacks
- Comparing Azure AI Foundry, Amazon Bedrock and Vertex AI
Organisation, Maturity and Investment Decisions
- Role split between platform team, ML engineering and product teams
- MLOps maturity levels and management KPIs
- Workshop: investment priority list for the organisation
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