Design enterprise ML platforms that scale across teams and clouds in this expert-level 5-day training with dedicated architecture labs.
The MLOps Architect Training Course is our most advanced offering, built for senior technologists who are responsible for designing and governing the ML infrastructure that entire organizations depend on. This is not a course about deploying individual models -- it is about designing platforms, systems, and standards that enable dozens of teams to develop, deploy, and operate ML at scale.
Over five intensive days, you will work through architecture design exercises covering ML platform blueprints, scalable pipeline frameworks, centralized feature platforms, multi-cloud deployment strategies, enterprise security and compliance architectures, and organizational enablement programs. Each module includes architecture lab sessions where you design and critique real platform architectures.
Enterprise architecture skills for building ML platforms that serve your entire organization.
Design internal ML platforms that provide self-service capabilities, standardized tooling, and shared infrastructure to accelerate ML adoption across all business units.
Architect pipeline frameworks that handle thousands of concurrent training jobs, manage resource contention, and scale horizontally with growing organizational demand.
Build a centralized feature platform that serves as the single source of truth for feature definitions, transformations, and serving across all ML projects in the organization.
Design cloud-agnostic ML architectures that avoid vendor lock-in, leverage best-of-breed services across providers, and support hybrid on-premises and cloud deployments.
Implement security architectures for ML systems covering data encryption, access controls, model provenance, vulnerability scanning, and enterprise compliance frameworks.
Create enablement programs that bring ML capabilities to every team, including developer experience, documentation, training curricula, and platform onboarding workflows.
For senior technologists shaping the future of ML infrastructure at their organizations.
Architects responsible for designing and evolving the internal ML platform, selecting technologies, and defining the reference architectures used by all ML teams.
Principal and staff engineers who set technical direction for ML infrastructure, make build-vs-buy decisions, and establish engineering standards across the organization.
Senior engineering leaders who need to understand ML platform architecture to make informed investment decisions and guide their teams on strategic technology choices.
Enterprise and cloud architects expanding their expertise to cover ML-specific infrastructure patterns, including multi-cloud strategies and hybrid deployment architectures.
5 Days / 40 Hours
8 hours per day
Live Virtual via Zoom
or In-Person Classroom
Design exercises with
expert architect feedback
Monday to Friday
9:00 AM - 5:00 PM
Six expert-level modules focused on platform design, architecture review, and organizational strategy.
This course is the definitive preparation path for the Certified MLOps Architect examination. The architecture labs mirror the design-oriented questions on the exam, and the curriculum covers every exam domain in depth. Your enrollment includes a certification exam voucher.
The Certified MLOps Architect is the pinnacle credential in the MLOps certification track. It validates your ability to design enterprise-scale ML platforms, make strategic technology decisions, and enable ML adoption across an entire organization. It is the credential that distinguishes platform leaders from practitioners.
View Certification DetailsOur premier training experience for architects shaping the future of enterprise ML.
Per participant
Limited to 15 participants per cohort. Contact us for private enterprise sessions.
Enroll today and build the skills that industry leaders demand.