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 Duration 14 hours

Course Outline

Fundamentals of Containerization for AI & ML

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

Managing Docker Images and Containers

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

Encapsulating ML Environments

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

Crafting Dockerfiles for Machine Learning

  • Designing Dockerfiles for ML projects
  • Optimal strategies for performance and maintenance
  • Implementation of multi-stage builds

Containerizing ML Models and Workflows

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

Executing Containerized ML Services

  • Configuring API endpoints for model inference
  • Expanding services using Docker Compose
  • Tracking runtime performance

Security and Regulatory Compliance

  • Safeguarding container configurations
  • Controlling access rights and credentials
  • Protecting sensitive ML assets

Rolling Out to Production Settings

  • Releasing images to container registries
  • Implementing containers in on-premises or cloud architectures
  • Managing versioning and updates for production services

Conclusion and Further Directions

Requirements

  • A solid grasp of machine learning processes
  • Proficiency in Python or comparable programming languages
  • Adequate knowledge of fundamental Linux command-line tasks

Intended Audience

  • ML engineers responsible for model deployment in production settings
  • Data scientists focused on maintaining reproducible experimental environments
  • AI developers creating 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

2026-11-19 09:30
14 hours
Athens
608 EUR (Online)
1008 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-03 09:30
14 hours
Kaminia
608 EUR (Online)
1008 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-17 09:30
14 hours
Thessaloniki
608 EUR (Online)
608 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-31 09:30
14 hours
Nicosia
608 EUR (Online)
608 EUR (Classroom)

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