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 Duration 21 hours

Course Outline

Foundations of GPU-Accelerated Containerization

  • The role of GPUs in deep learning workflows
  • How Docker facilitates GPU-centric tasks
  • Essential performance metrics to consider

Setup and Configuration of the NVIDIA Container Toolkit

  • Installing drivers and ensuring CUDA compatibility
  • Verifying GPU accessibility within containers
  • Configuring the execution environment

Creating GPU-Ready Docker Images

  • Incorporating CUDA base images
  • Encapsulating AI frameworks into GPU-ready containers
  • Handling dependencies for both training and inference phases

Executing GPU-Accelerated AI Tasks

  • Running training jobs with GPU support
  • Overseeing workloads that utilize multiple GPUs
  • Tracking GPU usage metrics

Enhancing Performance and Managing Resources

  • Applying limits and isolating GPU resources
  • Adjusting memory usage, batch sizes, and device assignment
  • Conducting performance tuning and diagnostics

Containerized Inference and Model Serving

  • Assembling containers prepared for inference
  • Handling high-demand workloads on GPUs
  • Connecting model runners with APIs

Scaling GPU Workloads via Docker

  • Approaches for distributed GPU training
  • Expanding the capacity of inference microservices
  • Managing AI systems composed of multiple containers

Security and Stability for GPU-Powered Containers

  • Safeguarding GPU access in shared settings
  • Strengthening the security posture of container images
  • Oversaw updates, version control, and compatibility

Conclusion and Future Directions

Requirements

  • A solid grasp of deep learning core concepts
  • Practical experience with Python and prevalent AI frameworks
  • Basic knowledge of containerization principles

Target Audience

  • Deep learning engineers
  • Research and development teams
  • Specialists in AI model training

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

2026-11-10 09:30
21 hours
Nantes, Zenith
3750 EUR (Online)
4350 EUR (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-11-24 09:30
21 hours
Clermont-Ferrand, ZI Le Brézet
3750 EUR (Online)
4350 EUR (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-12-08 09:30
21 hours
Bordeaux, Mériadeck
3750 EUR (Online)
4350 EUR (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-12-22 09:30
21 hours
Grenoble, Centre Ville Proche Gare
3750 EUR (Online)
11400 EUR (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2027-01-05 09:30
21 hours
Poitiers
3750 EUR (Online)
4350 EUR (Classroom)

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