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Duration 14 hours
Course Outline
Introduction to Containerization for AI & ML
- Fundamental concepts of containerization
- The suitability of containers for ML workloads
- Essential distinctions between containers and virtual machines
Working with Docker Images and Containers
- Comprehending images, layers, and registries
- Oversight of containers for ML experimentation
- Efficient utilization of the Docker CLI
Packaging ML Environments
- Readying ML codebases for containerization
- Administration of Python environments and dependencies
- Incorporation of CUDA and GPU support
Building Dockerfiles for Machine Learning
- Architecting Dockerfiles for ML projects
- Best practices for ensuring performance and maintainability
- Application of multi-stage builds
Containerizing ML Models and Pipelines
- Encapsulating trained models within containers
- Strategies for managing data and storage
- Implementation of reproducible end-to-end workflows
Running Containerized ML Services
- Creating API endpoints for model inference
- Service scaling utilizing Docker Compose
- Monitoring of runtime behavior
Security and Compliance Considerations
- Guaranteeing secure container configurations
- Control of access and credentials
- Management of confidential ML assets
Deploying to Production Environments
- Publication of images to container registries
- Container deployment in on-premises or cloud configurations
- Versioning and updating of production services
Summary and Next Steps
Requirements
- A solid grasp of machine learning workflows
- Proficiency in Python or equivalent programming languages
- Knowledge of fundamental Linux command-line operations
Target Audience
- ML engineers responsible for deploying models to production
- Data scientists focused on maintaining reproducible experiment environments
- AI developers creating scalable, container-based applications
Testimonials (2)
As i said before , for a person like me (no exp. ) this was a gateway to understanding features and functions with these programs/tools & etc. .
Patrick V. Duylovski - UBB + DZI (KBC GROUP)
Course - Docker and Kubernetes
multi-tiered, structured course programme.
