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 Duration 14 hours

Course Outline

Foundations of Containerization for AI & ML

  • Fundamental principles of containerization
  • The suitability of containers for ML workloads
  • Distinct advantages of containers over virtual machines

Managing Docker Images and Containers

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

Preparing ML Environments for Packaging

  • Readying ML codebases for containerization
  • Handling Python environments and dependencies
  • Incorporating CUDA and GPU support

Developing 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

  • Compacting trained models into containers
  • Strategies for managing data and storage
  • Implementing reproducible end-to-end workflows

Executing Containerized ML Services

  • Exposing API endpoints for model inference
  • Scaling services via Docker Compose
  • Monitoring runtime performance

Addressing Security and Compliance

  • Maintaining secure container configurations
  • Controlling access and credential management
  • Protecting sensitive ML assets

Production Deployment Strategies

  • Releasing images to container registries
  • Deploying containers in on-premise or cloud infrastructures
  • Version control and updating production services

Recap and Future Directions

Requirements

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

Target Audience

  • ML engineers responsible for model deployment in production
  • Data scientists overseeing reproducible experimental environments
  • AI developers constructing scalable, containerized 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

2026-11-13 09:30
14 hours
Montpellier, Garosud
2550 EUR (Online)
2950 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-11-27 09:30
14 hours
Nantes, Zenith
2550 EUR (Online)
2950 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-11 09:30
14 hours
Clermont-Ferrand, ZI Le Brézet
2550 EUR (Online)
2950 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-25 09:30
14 hours
Bordeaux, Mériadeck
2550 EUR (Online)
2950 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2027-01-08 09:30
14 hours
Grenoble, Centre Ville Proche Gare
2550 EUR (Online)
7650 EUR (Classroom)

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