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Course Outline
Introduction to Vertex AI for Enterprise Environments
- Enterprise AI requirements and associated challenges
- Overview of Vertex AI’s enterprise capabilities
- Applications in regulated industries
Establishing Enterprise MLOps Pipelines
- Integrating Vertex AI with CI/CD workflows
- Automation and orchestration strategies
- Practical lab: Constructing a deployment pipeline
Monitoring and Observability
- Real-time model monitoring and alerting mechanisms
- Performance dashboards for models
- Practical lab: Implementing monitoring workflows
Grounding and Gen AI Evaluation
- Anchoring models using enterprise data
- Gen AI evaluation libraries and associated tools
- Practical lab: Executing evaluation workflows
Compliance and Governance in Vertex AI
- Data residency and access control functionalities
- Auditability and traceability protocols
- Practical lab: Setting up compliance policies
Scaling and Enterprise Integration
- Expanding Vertex AI deployments at scale
- Integration with enterprise systems and APIs
- Practical lab: Enterprise-scale deployment scenarios
Case Studies and Best Practices
- Success stories from financial services, healthcare, and the public sector
- Insights gained from enterprise adoption
- Best practices for sustainable long-term operations
Conclusion and Future Steps
Requirements
- Practical experience in deploying ML models to production environments
- Proficiency with CI/CD pipelines
- Knowledge of data governance and compliance frameworks
Target Audience
- MLOps engineers
- Platform teams
- Compliance leads
14 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 2600 € + VAT*
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