Advance your expertise with this 5-day deep dive into production ML systems, experimentation frameworks, compliance, and performance optimization.
The MLOps Professional Training Course is an advanced program for experienced practitioners who already work with ML systems and want to take their skills to the next level. This course tackles the complex challenges that arise when ML systems operate at scale in production environments, where reliability, compliance, and performance are non-negotiable.
Across five days, you will master advanced topics such as designing rigorous A/B testing frameworks for model evaluation, implementing model governance and compliance workflows, optimizing inference performance for latency-sensitive applications, serving multiple models simultaneously, and building sophisticated monitoring systems that catch issues before they impact users.
Advanced skills for running reliable, compliant, and high-performance ML systems.
Design and operate ML systems that meet enterprise-grade requirements for availability, reliability, and scalability, including handling failure modes gracefully.
Implement statistically rigorous experimentation frameworks to compare model versions in production, including traffic splitting, metric selection, and significance testing.
Build end-to-end model governance workflows covering approval gates, audit logging, explainability requirements, and regulatory compliance documentation.
Apply model compression, quantization, caching strategies, and infrastructure tuning to reduce inference latency and increase throughput without sacrificing accuracy.
Manage concurrent model deployments including ensemble methods, model routing, shadow deployments, and resource isolation for multi-tenant serving environments.
Build comprehensive observability stacks covering data quality monitoring, prediction drift detection, custom metric dashboards, and automated alerting with root cause analysis.
For experienced practitioners ready to tackle advanced production challenges.
Experienced ML engineers who have deployed models to production and want to deepen their expertise in optimization, experimentation, and advanced serving patterns.
Data scientists moving beyond model development who want to own the full lifecycle including production deployment, monitoring, and performance optimization.
Practicing MLOps engineers seeking to advance their skills in governance automation, multi-model serving, and building enterprise-grade monitoring systems.
Technical leads responsible for the reliability and performance of ML systems who need to establish best practices and set technical direction for their teams.
5 Days / 40 Hours
8 hours per day
Live Virtual via Zoom
or In-Person Classroom
Cloud-based lab access
with GPU resources
Monday to Friday
9:00 AM - 5:00 PM
Six advanced modules with deep technical content and challenging lab exercises.
This course is the official preparation path for the Certified MLOps Professional examination. The curriculum maps directly to the exam domains, and the advanced labs provide the hands-on experience needed to tackle the scenario-based questions on the exam.
The Certified MLOps Professional credential signals deep expertise in running production ML systems at scale. It is designed for experienced practitioners who can demonstrate advanced competency in optimization, governance, experimentation, and monitoring.
View Certification DetailsTake the next step in your career with our most comprehensive technical training.
Per participant
Group discounts available for 5+ participants. Contact us for corporate pricing.
Enroll today and build the skills that industry leaders demand.