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.
Course Outline
Introduction to Vertex AI for Enterprise Use
- Key enterprise AI requirements and associated challenges.
- Overview of Vertex AI features tailored for enterprises.
- Relevant use cases in heavily regulated industries.
Building Enterprise MLOps Pipelines
- Connecting Vertex AI with CI/CD workflows.
- Strategies for automation and orchestration.
- Practical lab: Constructing a deployment pipeline.
Monitoring and Observability
- Implementing live model monitoring and alerting systems.
- Developing model performance dashboards.
- Practical lab: Configuring monitoring workflows.
Grounding and Gen AI Evaluation
- Anchoring models using enterprise data.
- Exploring Gen AI evaluation libraries and tools.
- Practical lab: Executing evaluation workflows.
Compliance and Governance in Vertex AI
- Features for data residency and access control.
- Ensuring auditability and traceability.
- Practical lab: Setting up compliance policies.
Scaling and Enterprise Integration
- Techniques for scaling Vertex AI deployments.
- Integration with broader enterprise systems and APIs.
- Practical lab: Enterprise-scale deployment execution.
Case Studies and Best Practices
- Success stories from financial services, healthcare, and the public sector.
- Key lessons learned during enterprise adoption.
- Best practices for sustainable long-term operations.
Summary and Next Steps
Requirements
- Practical experience in deploying ML models to production environments.
- Knowledge of CI/CD pipeline workflows.
- A solid understanding of data governance and compliance frameworks.
Target Audience
- MLOps engineers.
- Platform teams.
- Compliance leads.
14 Hours
Testimonials (1)
easy steps in ML
