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 Duration 14 hours

Course Outline

Foundations of Containerization for AI & ML

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

Managing Docker Images and Containers

  • Understanding images, layers, and registries
  • Using containers for ML experimentation
  • Efficient utilization 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
  • Utilizing multi-stage builds

Encapsulating ML Models and Pipelines

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

Operationalizing Containerized ML Services

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

Security and Compliance Protocols

  • Securing container configurations
  • Managing access controls and credentials
  • Protecting confidential ML assets

Production Deployment Strategies

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

Conclusion 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 responsible for deploying models to production
  • Data scientists focused on maintaining 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

Provisional Upcoming Courses (Require 5+ participants)

Containerized AI & ML Deployment with Docker

2026-11-16 09:30
14 hours
Ho Chi Minh City Saigon Tower
203,240,236 VND (Online)
203,246,536 VND (Classroom)

Containerized AI & ML Deployment with Docker

2026-11-30 09:30
14 hours
The Executive Centre - Saigon Centre Tower 1
203,240,236 VND (Online)
271,240,236 VND (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-14 09:30
14 hours
Hôtel des Arts Saigon
203,240,236 VND (Online)
203,240,236 VND (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-28 09:30
14 hours
Toong Oxygen
203,240,236 VND (Online)
203,240,236 VND (Classroom)

Containerized AI & ML Deployment with Docker

2027-01-11 09:30
14 hours
UPGen Le Meridien
203,240,236 VND (Online)
203,240,236 VND (Classroom)

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