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Course Outline
Fundamentals of Containerization in AI & ML
- Essential principles of containerization technology
- The suitability of containers for ML workloads
- Distinguishing features between containers and virtual machines
Interacting with Docker Images and Containers
- Concepts of images, layers, and registries
- Container management strategies for ML experimentation
- Efficient utilization of the Docker CLI
Encapsulating ML Environments
- Preparing ML codebases for containerization
- Overseeing Python environments and dependency management
- Incorporating CUDA and GPU support
Authoring Dockerfiles for Machine Learning
- Organizing Dockerfiles for ML projects
- Best practices for ensuring performance and maintainability
- Leveraging multi-stage builds
Containerizing ML Models and Pipelines
- Encapsulating trained models into containers
- Strategies for data and storage management
- Implementing reproducible end-to-end workflows
Executing Containerized ML Services
- Exposing API endpoints for model inference
- Scaling services utilizing Docker Compose
- Monitoring runtime behavior and performance
Security and Compliance Frameworks
- Implementing secure container configurations
- Managing access rights and credentials
- Protecting confidential ML assets
Production Deployment Strategies
- Releasing images to container registries
- Deploying containers in on-premise or cloud configurations
- Versioning and updating production services
Wrap-up and Future Directions
Requirements
- A solid grasp of machine learning workflows.
- Proficiency in Python or comparable programming languages.
- Basic familiarity with Linux command-line operations.
Intended Audience
- ML engineers responsible for deploying models into production.
- Data scientists tasked with managing reproducible experimental environments.
- AI developers focused on building 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
