Course Outline
Introduction to Containerization for AI & ML
- Core concepts of containerization.
- Why containers are ideal for ML workloads.
- Key differences between containers and virtual machines.
Working with Docker Images and Containers
- Understanding images, layers, and registries.
- Managing containers for ML experimentation.
- Utilizing the Docker CLI efficiently.
Packaging ML Environments
- Preparing ML codebases for containerization.
- Managing Python environments and dependencies.
- Integrating CUDA and GPU support.
Building Dockerfiles for Machine Learning
- Structuring Dockerfiles for ML projects.
- Best practices for performance and maintainability.
- Using multi-stage builds.
Containerizing ML Models and Pipelines
- Packaging trained models into containers.
- Managing data and storage strategies.
- Deploying reproducible end-to-end workflows.
Running Containerized ML Services
- Exposing API endpoints for model inference.
- Scaling services with Docker Compose.
- Monitoring runtime behavior.
Security and Compliance Considerations
- Ensuring secure container configurations.
- Managing access and credentials.
- Handling confidential ML assets.
Deploying 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 foundational understanding of machine learning workflows.
- Experience with Python or similar programming languages.
- Familiarity with basic Linux command-line operations.
Audience
- ML engineers responsible for deploying models to production.
- Data scientists managing reproducible experiment environments.
- AI developers building scalable containerized 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*
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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
