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 Duration 14 hours

Course Outline

Fundamentals of Containerization in AI & ML

  • Foundational principles of container technology
  • The suitability of containers for ML tasks
  • Distinctions between containers and virtual machines

Managing Docker Images and Containers

  • Comprehending images, layers, and registry structures
  • Oversight of containers for ML testing
  • Efficient utilization of the Docker CLI

Encapsulating ML Settings

  • Readying ML codebases for container integration
  • Oversight of Python settings and dependencies
  • Incorporation of CUDA and GPU capabilities

Crafting Dockerfiles for Machine Learning

  • Organizing Dockerfiles for ML initiatives
  • Optimal strategies for performance and upkeep
  • Utilization of multi-stage construction

Encapsulating ML Models and Workflows

  • Encapsulating trained models within containers
  • Oversight of data and storage methods
  • Implementation of repeatable, end-to-end processes

Executing Containerized ML Services

  • Publicizing API endpoints for model inference
  • Expanding services via Docker Compose
  • Observation of runtime activity

Security and Regulatory Aspects

  • Guaranteeing safe container setups
  • Oversight of access permissions and credentials
  • Protection of sensitive ML assets

Implementation in Production Settings

  • Release of images to container registries
  • Deployment of containers in on-premises or cloud infrastructures
  • Version control and updates for live services

Wrap-up and Future Directions

Requirements

  • A solid grasp of machine learning processes
  • Proficiency in Python or comparable programming languages
  • Basic familiarity with Linux command-line tasks

Target Audience

  • ML engineers responsible for moving models into production
  • Data scientists focused on maintaining reproducible experimental settings
  • AI developers creating scalable, containerized software solutions

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

2026-11-11 09:30
14 hours
Còrdoba - Ecipsa Tower
5980 USD (Online)
6980 USD (Classroom)

Containerized AI & ML Deployment with Docker

2026-11-25 09:30
14 hours
Puerto Madero - Torre Colonos Sur
5980 USD (Online)
6980 USD (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-09 09:30
14 hours
Buenos Aires - Laminar Catalinas
5980 USD (Online)
6980 USD (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-23 09:30
14 hours
Buenos Aires - Libertador
5980 USD (Online)
6980 USD (Classroom)

Containerized AI & ML Deployment with Docker

2027-01-06 09:30
14 hours
Còrdoba - Ecipsa Tower
5980 USD (Online)
6980 USD (Classroom)

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