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 Duration 14 hours

Course Outline

Fundamentals of Containerization for AI & ML

  • Essential principles of container technology
  • The suitability of containers for ML use cases
  • Distinguishing between containers and virtual machines

Managing Docker Images and Containers

  • Grasping images, layers, and registries
  • Overseeing containers for ML experimentation
  • Leveraging the Docker CLI effectively

Preparing ML Environments for Packaging

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

Creating Dockerfiles for Machine Learning

  • Architecting Dockerfiles for ML projects
  • Best practices for ensuring performance and maintainability
  • Utilizing multi-stage builds

Encapsulating ML Models and Pipelines

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

Operating Containerized ML Services

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

Addressing Security and Compliance

  • Configuring secure container settings
  • Controlling access and credential management
  • Safeguarding sensitive ML assets

Production Deployment Strategies

  • Distributing images via container registries
  • Implementing containers in on-prem or cloud infrastructures
  • Managing versions and updating live services

Conclusion and Future Pathways

Requirements

  • Foundational knowledge of machine learning workflows.
  • Proficiency in Python or comparable programming languages.
  • Basic familiarity with Linux command-line operations.

Who This Course Is For

  • ML engineers responsible for moving models into production.
  • Data scientists seeking to maintain reproducible experimental environments.
  • AI developers aiming to build 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
Pune, SB Road - Classroom
168,661 INR (Online)
174,061 INR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-02 09:30
14 hours
Pune, Koregaon Park - T1
168,661 INR (Online)
178,661 INR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-16 09:30
14 hours
Delhi, Connaught Place - Classroom
168,661 INR (Online)
178,661 INR (Classroom)

Containerized AI & ML Deployment with Docker

2026-12-30 09:30
14 hours
Delhi, Mohan Estate Metro Station - Classroom
168,661 INR (Online)
174,661 INR (Classroom)

Containerized AI & ML Deployment with Docker

2027-01-13 09:30
14 hours
Hyderabad, Banjara Hills - Classroom
168,661 INR (Online)
177,661 INR (Classroom)

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