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Course Outline
Introduction to Containerization in AI & ML
- Fundamental concepts of containerization
- The suitability of containers for ML workloads
- Distinguishing between containers and virtual machines
Managing Docker Images and Containers
- Gaining insight into images, layers, and registries
- Overseeing containers for ML experimentation
- Leveraging the Docker CLI for efficiency
Preparing ML Environments for Packaging
- Preparing ML codebases for containerization
- Handling Python environments and dependencies
- Incorporating CUDA and GPU support
Crafting Dockerfiles for Machine Learning
- Organizing Dockerfiles for ML projects
- Adhering to best practices for performance and maintainability
- Utilizing multi-stage builds
Containerizing ML Models and Pipelines
- Encapsulating trained models into containers
- Handling data and storage strategies
- Implementing reproducible end-to-end workflows
Executing Containerized ML Services
- Creating API endpoints for model inference
- Expanding services using Docker Compose
- Observing runtime behavior
Addressing Security and Compliance
- Configuring secure containers
- Controlling access and managing credentials
- Protecting sensitive ML assets
Production Environment Deployment
- Releasing images to container registries
- Installing containers in on-premises or cloud configurations
- Managing versions and updates for production services
Wrap-up and Future Actions
Requirements
- A foundational understanding of machine learning workflows
- Practical experience with Python or equivalent programming languages
- Proficiency in basic Linux command-line operations
Target Audience
- ML engineers responsible for deploying models to production
- Data scientists focused on managing reproducible experiment environments
- AI developers building scalable, containerized applications
14 Hours
Testimonials (1)
The training met expectations with its clear explanations, real-world examples, and hands-on labs that made complex topics easy to understand. It provided valuable insights into container orchestration, security, scaling and many other advanced topics.
