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 Duration 14 hours

Course Outline

Foundations of Containerization for AI & ML

  • Essential principles of containerization
  • The suitability of containers for ML workloads
  • Distinguishing between containers and virtual machines

Manipulating Docker Images and Containers

  • Comprehending images, layers, and registries
  • Oversight of containers for ML experimentation
  • Efficient utilization of the Docker CLI

Packaging ML Environments

  • Ready state preparation of ML codebases for containerization
  • Management of Python environments and dependencies
  • Incorporation of CUDA and GPU support

Creating Dockerfiles for Machine Learning

  • Architecting Dockerfiles for ML projects
  • Best practices for ensuring performance and maintainability
  • Leveraging multi-stage builds

Encapsulating ML Models and Pipelines

  • Wrapping trained models within containers
  • Strategies for managing data and storage
  • Rolling out reproducible end-to-end workflows

Executing Containerized ML Services

  • Opening API endpoints for model inference
  • Scaling services utilizing Docker Compose
  • Monitoring runtime behavior

Security and Compliance Factors

  • Safeguarding container configurations
  • Administration of access controls and credentials
  • Protection of confidential ML assets

Production Environment Deployment

  • Releasing images to container registries
  • Implementing containers in on-premises or cloud configurations
  • Version control and updating of production services

Conclusion and Future Recommendations

Requirements

  • A solid grasp of machine learning workflows
  • Proficiency in Python or comparable programming languages
  • Basic command of the Linux command-line interface

Target Audience

  • ML engineers responsible for production model deployment
  • Data scientists ensuring reproducibility in experimental environments
  • AI developers creating scalable, container-based applications

Number of participants


Price per participant

Open Training Courses require 5+ participants.

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.

Bert Paelinckx - Cube SoftwareSolutions
Course - Introduction to Docker

Upcoming Courses

Containerized AI & ML Deployment with Docker

2026-11-25 09:30
14 hours
København, Copenhagen
3472 EUR (Online)
3872 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-09 09:30
14 hours
Copenhagen, City Center
3472 EUR (Online)
3872 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-23 09:30
14 hours
København, Copenhagen
3472 EUR (Online)
3872 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2027-01-06 09:30
14 hours
Copenhagen, City Center
3472 EUR (Online)
3872 EUR (Classroom)

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