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Course Outline
Introduction to Containerization for AI and ML
- Fundamental principles of containerization
- The suitability of containers for ML workloads
- Distinct differences between containers and virtual machines
Managing Docker Images and Containers
- Comprehending images, layers, and registries
- Handling containers for ML experimentation
- Efficiently utilizing the Docker CLI
Packaging ML Environments
- Preparing ML codebases for containerization
- Managing Python environments and their dependencies
- Integrating CUDA and GPU support
Creating Dockerfiles for Machine Learning
- Structuring Dockerfiles for ML projects
- Best practices for maintaining performance and maintainability
- Utilizing multi-stage builds
Containerizing ML Models and Pipelines
- Packaging trained models within containers
- Managing data and storage strategies
- Deploying reproducible end-to-end workflows
Running Containerized ML Services
- Exposing API endpoints for model inference
- Scaling services using Docker Compose
- Monitoring runtime behaviour
Security and Compliance Considerations
- Ensuring secure container configurations
- Managing access controls and credentials
- Handling confidential ML assets
Deploying to Production Environments
- Publishing images to container registries
- Deploying containers in on-premises or cloud configurations
- Versioning and updating production services
Summary and Next Steps
Requirements
- Knowledge of machine learning workflows
- Proficiency in Python or similar programming languages
- Familiarity with fundamental Linux command-line operations
Target Audience
- ML engineers deploying models into production
- Data scientists managing reproducible experimental environments
- AI developers constructing scalable containerized applications
14 Hours
Testimonials (3)
How trainer deliver knowledge so effectively
Vu Thoai Le - Reply Polska sp. z o. o.
Course - Certified Kubernetes Administrator (CKA) - exam preparation
the trainer had a lot of knowledge and patience to share with us
Bogdan Olaru
Course - Introduction to Docker
The knowledge and exchanges with Augustin
