MLOps Engineer

Overview

This course focuses on deploying and operating AI models with full EU AI Act traceability and compliance. It equips MLOps engineers with the practical skills needed to implement robust logging, versioning, monitoring, and drift detection for high-risk AI systems.

What You Will Learn

• Implement Article 12 logging requirements for automatic recording
• Maintain configuration baselines as required in Annex IV sec.5
• Set up effective drift detection and alerting mechanisms
• Establish compliant model deployment and ongoing monitoring processes

Who Should Take This Course

This course is designed for MLOps Engineers, Machine Learning Operations Specialists, DevOps Engineers for AI, Platform Engineers, and technical professionals responsible for deploying and monitoring production AI systems.

Course Format

AI Assurance E-Learning Platform - Self-paced online.

Key Benefits

• Ability to deploy AI models in a fully compliant and traceable manner
• Practical skills for logging, versioning, and drift monitoring
• Structured approach to meeting Article 12 and Annex IV requirements
• Confidence in maintaining operational compliance throughout the model lifecycle

Body of Knowledge - Mapped to Standards and Regulations

• Article 12 Logging (automatic recording requirements, EU AI Act Article 12)
• Versioning & Configuration (model registry, baseline management, Annex IV sec.5)
• Monitoring & Drift (real-time monitoring setup, Article 72 obligations)

Key Takeaways

• Understanding of the MLOps Engineer role and responsibilities
• Core knowledge and practical skills for compliant model operations
• Clarity on risk and control responsibilities
• Awareness of key duties and performance indicators for the role

Certificate

Participants will receive a certificate of completion upon finishing the course.