Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Foundations of Vertex AI for Enterprise Environments
- Key AI requirements and business challenges
- Overview of enterprise-specific features in Vertex AI
- Applications within regulated industries
Building Enterprise MLOps Pipelines
- Connecting Vertex AI with CI/CD processes
- Techniques for automation and orchestration
- Practical exercise: Constructing a deployment pipeline
Monitoring and System Observability
- Real-time model monitoring and alert mechanisms
- Utilizing performance dashboards
- Practical exercise: Configuring monitoring workflows
Model Grounding and Gen AI Assessment
- Anchoring models with proprietary enterprise data
- Exploring Gen AI evaluation libraries and utilities
- Practical exercise: Executing evaluation workflows
Compliance and Governance Frameworks
- Features for data residency and access management
- Ensuring auditability and traceability
- Practical exercise: Setting up compliance policies
Scaling and Corporate Integration
- Expanding Vertex AI deployments at scale
- Connecting with corporate systems and APIs
- Practical exercise: Enterprise-level deployment
Real-World Case Studies and Industry Best Practices
- Success narratives in finance, healthcare, and the public sector
- Key takeaways from enterprise adoption journeys
- Strategies for sustainable long-term operations
Wrap-up and Future Recommendations
Requirements
- Practical experience in deploying ML models into production environments
- Proficiency with CI/CD workflows
- Knowledge of data governance and compliance standards
Target Audience
- MLOps engineers
- Platform engineering teams
- Compliance officers and leads
Testimonials (1)
easy steps in ML
