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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
  • Key distinctions between containers and virtual machines

Managing Docker Images and Containers

  • Comprehending images, layers, and registries
  • Container management for ML experimentation
  • Efficient utilization 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

  • Designing Dockerfiles for ML projects
  • Best practices for performance and maintainability
  • Utilizing multi-stage builds

Containerizing ML Models and Pipelines

  • Packaging trained models within containers
  • Managing data and storage strategies
  • Implementing reproducible end-to-end workflows

Operationalizing Containerized ML Services

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

Security and Compliance Considerations

  • Ensuring secure container configurations
  • Managing access controls and credentials
  • Safeguarding confidential ML assets

Production Deployment Strategies

  • Publishing images to container registries
  • Deploying containers in on-premises or cloud setups
  • Versioning and updating production services

Course Summary and Next Steps

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 deploying models to production
  • Data scientists focused on managing reproducible experimental environments
  • AI developers constructing 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
Business Center Plovdiv
540 EUR (Online)
2240 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-09 09:30
14 hours
Crystal Business Center
540 EUR (Online)
940 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-23 09:30
14 hours
Central Point Varna
540 EUR (Online)
940 EUR (Classroom)

Containerized AI & ML Deployment with Docker

2027-01-06 09:30
14 hours
Business Center Plovdiv
540 EUR (Online)
2240 EUR (Classroom)

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