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 Duration 14 hours

Course Outline

Foundations of Containerization for AI & ML

  • Essential principles of containerization
  • The advantages of containers for ML workloads
  • Distinguishing containers from virtual machines

Handling Docker Images and Containers

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

Encapsulating ML Environments

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

Creating Dockerfiles for Machine Learning

  • Organizing Dockerfiles for ML projects
  • Best practices for performance and upkeep
  • Implementing multi-stage builds

Containerizing ML Models and Pipelines

  • Encapsulating trained models into containers
  • Managing data and storage approaches
  • Rolling out reproducible end-to-end processes

Executing Containerized ML Services

  • Opening API endpoints for model inference
  • Scaling services via Docker Compose
  • Monitoring runtime performance

Security and Compliance Focus

  • Safeguarding container configurations
  • Controlling access and credentials
  • Protecting confidential ML assets

Implementing in Production Settings

  • Releasing images to container registries
  • Deploying containers in on-prem or cloud contexts
  • Versioning and refreshing production services

Recap and Future Directions

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 focused on production model deployment
  • Data scientists seeking 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

2026-11-18 09:30
14 hours
Empire Tower
63214 THB (Online)
63214 THB (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-02 09:30
14 hours
Empire Tower
63214 THB (Online)
63214 THB (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-16 09:30
14 hours
Empire Tower
63214 THB (Online)
63214 THB (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-30 09:30
14 hours
Empire Tower
63214 THB (Online)
63214 THB (Classroom)

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