Course Outline
Introduction to Containerisation for AI & ML
- Core principles of containerisation
- The suitability of containers for ML workloads
- Distinctions between containers and virtual machines
Utilising Docker Images and Containers
- Comprehending images, layers, and registries
- Managing containers for ML experimentation
- Efficient use of the Docker CLI
Encapsulating ML Environments
- Preparing ML codebases for containerisation
- Administering Python environments and dependencies
- Incorporating CUDA and GPU support
Authoring Dockerfiles for Machine Learning
- Structuring Dockerfiles for ML projects
- Best practices for performance and maintainability
- Implementing multi-stage builds
Containerising ML Models and Pipelines
- Packaging trained models into containers
- Managing data and storage strategies
- Implementing reproducible end-to-end workflows
Operationalising Containerised ML Services
- Exposing API endpoints for model inference
- Scaling services with Docker Compose
- Monitoring runtime behaviour
Security and Compliance Considerations
- Ensuring secure container configurations
- Administering access and credentials
- Securing confidential ML assets
Deployment to Production Environments
- Publishing images to container registries
- Deploying containers in on-prem or cloud setups
- Versioning and updating production services
Summary and Next Steps
Requirements
- A solid understanding of machine learning workflows.
- Proficiency in Python or comparable programming languages.
- Familiarity with fundamental Linux command-line operations.
Target Audience
- ML engineers responsible for deploying models to production.
- Data scientists maintaining reproducible experiment environments.
- AI developers creating scalable containerised applications.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 2600 € + VAT*
Contact us for an exact quote and to hear our latest promotions
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.
