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 Duration 21 hours

Course Outline

Foundations of GPU-Accelerated Containerization

  • Exploring the role of GPUs in deep learning pipelines
  • The mechanism by which Docker enables GPU-based tasks
  • Critical factors impacting performance

Setup and Configuration of the NVIDIA Container Toolkit

  • Installing drivers and establishing CUDA compatibility
  • Verifying GPU accessibility within containers
  • Tailoring the runtime environment settings

Creating GPU-Enabled Docker Images

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

Executing GPU-Accelerated AI Workloads

  • Running training jobs on GPU hardware
  • Orchestrating multi-GPU workloads
  • Tracking and monitoring GPU usage

Enhancing Performance and Resource Management

  • Constraining and isolating GPU resources
  • Refining memory usage, batch sizes, and device allocation
  • Conducting performance tuning and diagnostic analysis

Containerized Inference and Model Deployment

  • Constructing containers optimized for inference
  • Handling high-throughput workloads on GPUs
  • Integrating model runners with API interfaces

Scaling GPU Operations with Docker

  • Approaches for distributed GPU training
  • Expanding inference microservices
  • Orchestrating complex multi-container AI systems

Securing and Stabilizing GPU-Enabled Containers

  • Securing GPU access in shared operational environments
  • Strengthening the security of container images
  • Managing updates, version control, and compatibility

Conclusion and Future Directions

Requirements

  • A solid grasp of deep learning core concepts
  • Practical experience with Python and standard AI frameworks
  • Knowledge of fundamental 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

2026-11-18 09:30
21 hours
Ankara
29025 TRY (Online)
29625 TRY (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-12-02 09:30
21 hours
Antalya
29025 TRY (Online)
29625 TRY (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-12-16 09:30
21 hours
Istanbul, Taksim
29025 TRY (Online)
29625 TRY (Classroom)

GPU-Accelerated AI & Deep Learning with Docker Containers

2026-12-30 09:30
21 hours
Ankara
29025 TRY (Online)
29625 TRY (Classroom)

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