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Course Outline
Introduction to Containerization for AI & ML
- Fundamental concepts of containerization.
- The suitability of containers for ML workloads.
- Distinguishing key differences between containers and virtual machines.
Working with Docker Images and Containers
- Comprehending images, layers, and registries.
- Managing containers to facilitate ML experimentation.
- Efficient use of the Docker CLI.
Packaging ML Environments
- Preparing ML codebases for containerization.
- Managing Python environments and associated dependencies.
- Integrating CUDA and GPU support.
Building Dockerfiles for Machine Learning
- Structuring Dockerfiles effectively for ML projects.
- Best practices for ensuring performance and maintainability.
- Utilizing multi-stage builds.
Containerizing ML Models and Pipelines
- Encapsulating trained models into containers.
- Implementing strategies for data and storage management.
- Deploying reproducible end-to-end workflows.
Running Containerized ML Services
- Exposing API endpoints for model inference.
- Scaling services using Docker Compose.
- Monitoring runtime behavior.
Security and Compliance Considerations
- Ensuring secure container configurations.
- Managing access controls and credentials.
- Handling confidential ML assets securely.
Deploying to Production Environments
- Publishing images to container registries.
- Deploying containers in on-premises or cloud setups.
- Versioning and updating production services.
Summary and Next Steps
Requirements
- A solid understanding of machine learning workflows.
- Experience working with Python or comparable programming languages.
- Familiarity with basic Linux command-line operations.
Target Audience
- ML engineers responsible for deploying models to production.
- Data scientists who need to manage reproducible experiment 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
