Course Outline

Introduction to Mistral Medium 3 for Government

  • Model Architecture and Capabilities
  • Comparison with Other Mistral Models
  • Key Applications for Government

Deployment Strategies for Government

  • API-Based Deployment
  • Self-Hosting with Docker and Kubernetes
  • Hybrid and Multi-Cloud Considerations for Government

Performance Optimization for Government

  • Batching and Parallelization Techniques
  • Model Quantization and Acceleration
  • Cost-Performance Tradeoffs for Government Operations

Multimodal Applications for Government

  • Integrating Text and Image Processing for Government Services
  • OCR and Document Intelligence for Government Records
  • Cross-Modal Enterprise Workflows for Government Agencies

Security and Compliance for Government

  • Data Residency and Privacy Considerations for Government Data
  • Role-Based Access and Permissions for Government Users
  • Auditability and Governance for Government Operations

Monitoring and Observability for Government

  • Tracking Performance and Drift in Government Systems
  • Logging and Metrics Pipelines for Government IT
  • Alerting and Troubleshooting for Government Applications

Scaling for Enterprise for Government

  • Horizontal and Vertical Scaling Patterns for Government Infrastructure
  • Load Balancing and Redundancy for Government Services
  • Disaster Recovery Strategies for Government Operations

Summary and Next Steps for Government

Requirements

  • Proficiency in Python or a comparable programming language
  • Experience with the deployment of machine learning models
  • Understanding of cloud-based or containerized environments

Audience

  • AI/ML engineers for government
  • Platform architects for government
  • MLOps teams for government
 14 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories