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 Mistral Medium 3
- Model architecture and core capabilities
- Benchmarking against other Mistral models
- Primary enterprise applications
Deployment Strategies
- API-centric deployment methods
- Self-hosting using Docker and Kubernetes
- Hybrid and multi-cloud deployment considerations
Performance Optimization
- Techniques for batching and parallelization
- Model quantization and acceleration methods
- Balancing cost versus performance
Multimodal Applications
- Integration of text and image processing
- OCR and document intelligence solutions
- Building cross-modal enterprise workflows
Security and Compliance
- Data residency and privacy requirements
- Role-based access control and permissions
- Ensuring auditability and governance
Monitoring and Observability
- Tracking performance metrics and model drift
- Constructing logging and metrics pipelines
- Setting up alerting and troubleshooting mechanisms
Enterprise Scaling
- Horizontal and vertical scaling architectures
- Load balancing and redundancy implementation
- Disaster recovery planning
Summary and Next Steps
Requirements
- Strong proficiency in Python or equivalent programming languages
- Practical experience in deploying machine learning models
- Familiarity with cloud or containerized environments
Target Audience
- AI/ML Engineers
- Platform Architects
- MLOps Teams
14 Hours
