Professional Training · Applied AI Engineering Track
LLMOps: Operationalising Generative AI
Learn to run generative AI systems reliably in production. The course covers deployment patterns, cost and latency management, evaluation pipelines, observability and incident response for LLM-powered applications at scale.
Authorised Instructors
Eric Tai
Head, Technology
- Security – Specialty
- DevOps Engineer – Professional
- Solutions Architect – Professional
- CloudOps Engineer – Associate
- +4 more
Hui Liang
Chief Digital Officer
- Security – Specialty
- Generative AI Developer – Professional
- Solutions Architect – Professional
- CloudOps Engineer – Associate
- +5 more
Any of these AWS Authorised Instructors may deliver this class, depending on the scheduled run. Trainers confirmed on enrolment.
Who Should Attend
- Platform Engineers: Engineers running shared infrastructure for AI workloads.
- MLOps Engineers: Practitioners automating deployment and monitoring of models.
- DevOps Engineers: Engineers extending CI/CD pipelines to cover LLM applications.
- Site Reliability Engineers: SREs responsible for availability of AI-powered services.
- Engineering Leads: Leads setting operational standards for generative AI systems.
Prerequisites
This is an advanced course. To attend, you should have:
Working knowledge of containers and CI/CD pipelines.
Experience operating production services.
Familiarity with LLM APIs or agent frameworks.
Learning Objectives
In this course, you will learn to:
Deploy LLM workloads: Select and configure deployment patterns for cost and scale.
Build evaluation pipelines: Continuously test model and prompt quality pre- and post-release.
Monitor and observe: Track latency, cost, drift and failure modes in production.
Automate rollouts: Apply progressive delivery to model and prompt changes.
Respond to incidents: Diagnose and recover from generative AI production issues.
Certification
This course does not map to a vendor certification exam. It equips platform and engineering teams to run generative AI in production with the same rigour as any other critical service. Every participant receives a My Code Campus certificate of completion.
In-person in Kuala Lumpur or live virtual. Team & enterprise rates available.
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