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 Duration 14 hours

Course Outline

Foundations of Containerization in AI & ML

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

Utilizing Docker Images and Containers

  • Comprehending images, layers, and registries
  • Container management for ML experimentation
  • Efficient use of the Docker CLI

Encapsulating ML Environments

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

Creating Dockerfiles for Machine Learning

  • Organizing Dockerfiles for ML projects
  • Best practices for performance and maintainability
  • Employing multi-stage builds

Containerizing ML Models and Pipelines

  • Packaging trained models into containers
  • Data and storage strategy management
  • Implementing reproducible end-to-end workflows

Executing Containerized ML Services

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

Security and Compliance Aspects

  • Securing container configurations
  • Managing access controls and credentials
  • Protecting confidential ML assets

Deployment to Production Settings

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

Conclusion and Future Directions

Requirements

  • A grasp of machine learning workflows
  • Proficiency in Python or comparable programming languages
  • Knowledge of fundamental Linux command-line interactions

Target Audience

  • ML engineers responsible for model deployment to production
  • Data scientists requiring reproducible experiment 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

2026-11-23 09:30
14 hours
Brno
3000 EUR (Online)
3000 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-07 09:30
14 hours
Ostrava
3000 EUR (Online)
3000 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-21 09:30
14 hours
Prague, Prague Castle
3000 EUR (Online)
3400 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2027-01-04 09:30
14 hours
Brno
3000 EUR (Online)
3000 EUR (Classroom)

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