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 Duration 21 hours

Course Outline

Introduction to GPU-Accelerated Containerization

  • Exploring the role of GPUs in deep learning pipelines
  • How Docker facilitates GPU-based workloads
  • Essential performance factors to consider

Installing and Configuring the NVIDIA Container Toolkit

  • Setting up drivers and ensuring CUDA compatibility
  • Verifying GPU access within containers
  • Configuring the necessary runtime environment

Creating GPU-Enabled Docker Images

  • Utilizing CUDA base images
  • Packaging AI frameworks into GPU-ready containers
  • Managing dependencies for training and inference

Executing GPU-Accelerated AI Workloads

  • Running training jobs with GPU support
  • Handling multi-GPU workloads
  • Tracking GPU utilization metrics

Enhancing Performance and Resource Allocation

  • Controlling and isolating GPU resources
  • Tuning memory, batch sizes, and device placement
  • Performance tuning and diagnostic techniques

Containerized Inference and Model Serving

  • Developing containers ready for inference
  • Serving high-volume workloads on GPUs
  • Integrating model runners and API interfaces

Scaling GPU Workloads with Docker

  • Strategies for distributed GPU training
  • Scaling inference microservices
  • Coordinating multi-container AI systems

Security and Reliability for GPU-Enabled Containers

  • Ensuring secure GPU access in shared environments
  • Hardening container images for security
  • Managing updates, versioning, and compatibility

Summary and Future Steps

Requirements

  • A solid grasp of deep learning fundamentals
  • Practical experience with Python and standard AI frameworks
  • Basic familiarity with containerization principles

Target Audience

  • Deep learning engineers
  • Research and development teams
  • AI model trainers

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

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-11-19 09:30
21 hours
Nicosia
911 EUR (Online)
911 EUR (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-12-03 09:30
21 hours
Nicosia
911 EUR (Online)
1511 EUR (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-12-17 09:30
21 hours
Athens
911 EUR (Online)
1511 EUR (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-12-31 09:30
21 hours
Kaminia
911 EUR (Online)
1511 EUR (Classroom)

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