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 Duration 14 hours

Course Outline

Foundations of Containerization for AI & ML

  • Essential concepts of containerization
  • The advantages of containers for ML workloads
  • Distinguishing between containers and virtual machines

Interacting with Docker Images and Containers

  • Comprehending images, layers, and registries
  • Overseeing containers for ML experimentation
  • Leveraging the Docker CLI for efficiency

Encapsulating ML Environments

  • Ready ML codebases for containerization
  • Controlling Python environments and dependencies
  • Incorporating CUDA and GPU support

Crafting Dockerfiles for Machine Learning

  • Organizing Dockerfiles for ML projects
  • Adhering to best practices for performance and maintainability
  • Implementing multi-stage builds

Containerizing ML Models and Pipelines

  • Encapsulating trained models into containers
  • Overseeing data and storage strategies
  • Establishing reproducible end-to-end workflows

Executing Containerized ML Services

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

Security and Compliance Essentials

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

Deployment to Production Environments

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

Conclusion and Future Directions

Requirements

  • A solid grasp of machine learning workflows
  • Proficiency in Python or comparable programming languages
  • Familiarity with fundamental Linux command-line operations

Target Audience

  • ML engineers responsible for deploying models to production
  • Data scientists focused on managing 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

2026-11-23 09:30
14 hours
Bayan Lepas, iDEAL
14441 MYR (Online)
14931 MYR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-07 09:30
14 hours
Kuala Lumpur KL Sentral
14441 MYR (Online)
15091 MYR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-21 09:30
14 hours
Bayan Lepas, iDEAL
14441 MYR (Online)
14931 MYR (Classroom)

Containerized AI & ML Deployment with Docker

2027-01-04 09:30
14 hours
Kuala Lumpur KL Sentral
14441 MYR (Online)
15091 MYR (Classroom)

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