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 Duration 14 hours

Course Outline

Foundations of Containerization for AI & ML

  • Fundamental concepts 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
  • Overseeing containers for ML experimentation
  • Efficient utilization of the Docker CLI

Preparing ML Environments for Packaging

  • Ready ML codebases for containerization
  • Oversight of Python environments and dependencies
  • Integration of CUDA and GPU support

Creating Dockerfiles for Machine Learning

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

Encapsulating ML Models and Pipelines

  • Packaging trained models into containers
  • Strategies for data and storage management
  • Implementation of reproducible end-to-end workflows

Executing Containerized ML Services

  • Creating API endpoints for model inference
  • Scaling services using Docker Compose
  • Observing runtime behavior

Security and Compliance Considerations

  • Ensuring secure container configurations
  • Management of access controls and credentials
  • Handling of confidential ML assets

Deployment to Production Environments

  • Publishing images to container registries
  • Implementing containers in on-prem or cloud architectures
  • Version control and updating of production services

Wrap-up and Future Directions

Requirements

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

Intended Audience

  • ML engineers responsible for deploying models into production
  • Data scientists maintaining 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

2026-11-16 09:30
14 hours
Riga, Old Town
3000 EUR (Online)
3400 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-11-30 09:30
14 hours
Riga, Old Town
3000 EUR (Online)
3400 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-14 09:30
14 hours
Riga, Old Town
3000 EUR (Online)
3400 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-28 09:30
14 hours
Riga, Old Town
3000 EUR (Online)
3400 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2027-01-11 09:30
14 hours
Riga, Old Town
3000 EUR (Online)
3400 EUR (Classroom)

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