Course Outline

Introduction to Vertex AI for the Enterprise

  • Enterprise AI requirements and challenges
  • Vertex AI enterprise features overview
  • Use cases in regulated industries

Setting Up Enterprise MLOps Pipelines

  • Integrating Vertex AI with CI/CD workflows
  • Automation and orchestration
  • Hands-on lab: building a deployment pipeline

Monitoring and Observability

  • Live model monitoring and alerting
  • Model performance dashboards
  • Hands-on lab: setting up monitoring workflows

Grounding and Gen AI Evaluation

  • Grounding models with enterprise data
  • Gen AI evaluation libraries and tools
  • Hands-on lab: implementing evaluation workflows

Compliance and Governance in Vertex AI

  • Data residency and access control features
  • Auditability and traceability
  • Hands-on lab: configuring compliance policies

Scaling and Enterprise Integration

  • Scaling Vertex AI deployments
  • Integration with enterprise systems and APIs
  • Hands-on lab: enterprise-scale deployment

Case Studies and Best Practices

  • Success stories in financial services, healthcare, and public sector
  • Lessons learned in enterprise adoption
  • Best practices for long-term operations

Summary and Next Steps

Requirements

  • Experience with deploying ML models in production
  • Familiarity with CI/CD pipelines
  • Understanding of data governance and compliance frameworks

Audience

  • MLops engineers
  • Platform teams
  • Compliance leads
 14 Hours

Delivery Options

Private Group Training

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  • Pre-course call with your trainer
  • Customisation of the learning experience to achieve your goals -
    • Bespoke outlines
    • Practical hands-on exercises containing data / scenarios recognisable to the learners
  • Training scheduled on a date of your choice
  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

Private Group Prices RRP from £3800 online delivery, based on a group of 2 delegates, £1200 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

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