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 Duration 14 hours

Course Outline

Introduction to Containerization for AI & ML

  • Fundamental principles of containerization
  • The suitability of containers for ML workloads
  • Distinguishing between containers and virtual machines

Managing Docker Images and Containers

  • Grasping images, layers, and registries
  • Utilizing containers for ML experimentation
  • Efficient use of the Docker CLI

Packaging 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
  • Implementing multi-stage builds

Containerizing ML Models and Pipelines

  • Encapsulating trained models in containers
  • Strategizing data and storage management
  • Deploying reproducible end-to-end workflows

Executing Containerized ML Services

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

Security and Compliance Considerations

  • Configuring secure containers
  • Managing access controls and credentials
  • Safeguarding confidential ML assets

Production Deployment

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

Conclusion and Future 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 seeking to manage reproducible experiment 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

2026-11-20 10:00
14 hours
Seoul Center 1
₩ 5000000 (Online)
₩ 10000000 (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-04 10:00
14 hours
Jungang-Dong Center
₩ 5000000 (Online)
₩ 10000000 (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-18 10:00
14 hours
Seoul - Gran Seoul
₩ 5000000 (Online)
₩ 10000000 (Classroom)

Containerized AI & ML Deployment with Docker

2027-01-01 10:00
14 hours
Seoul Center 1
₩ 5000000 (Online)
₩ 10000000 (Classroom)

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