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 Duration 21 hours

Course Outline

Introduction to GPU-Accelerated Containerization

  • Exploring GPU utilization in deep learning workflows
  • Understanding how Docker facilitates GPU-based workloads
  • Identifying key performance considerations

Installing and Configuring the NVIDIA Container Toolkit

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

Constructing GPU-Enabled Docker Images

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

Executing GPU-Accelerated AI Workloads

  • Running training jobs using GPUs
  • Managing multi-GPU workloads
  • Monitoring GPU utilization

Performance and Resource Allocation Optimization

  • Limiting and isolating GPU resources
  • Optimizing memory, batch sizes, and device placement
  • Performance tuning and diagnostics

Containerized Inference and Model Serving

  • Building inference-ready containers
  • Serving high-load workloads on GPUs
  • Integrating model runners and APIs

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
  • Managing updates, versions, and compatibility

Summary and Next Steps

Requirements

  • A solid grasp of deep learning fundamentals
  • Proficiency in Python and common AI frameworks
  • Basic knowledge of containerization concepts

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

2026-11-30 09:30
21 hours
Riga, Old Town
4500 EUR (Online)
5100 EUR (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-12-14 09:30
21 hours
Riga, Old Town
4500 EUR (Online)
5100 EUR (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-12-28 09:30
21 hours
Riga, Old Town
4500 EUR (Online)
5100 EUR (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2027-01-11 09:30
21 hours
Riga, Old Town
4500 EUR (Online)
5100 EUR (Classroom)

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