GPU Acceleration Courses and Certifications

Institute for Pure & Applied Mathematics (IPAM)

Scaling NumPy Applications from 1 CPU to Thousands of GPUs - IPAM at UCLA

Discover cuNumeric: a NumPy replacement enabling Python applications to scale across multiple nodes and leverage GPU acceleration for enhanced performance and dataset handling.

• YouTube
• 37 minutes
• On-Demand
• Free Video

Nvidia

GPU-Acceleration for Pandas, NetworkX, and Apache Spark MLlib - Accelerating Data Science Tools

Discover GPU-accelerated data science tools for pandas, NetworkX, and Apache Spark MLlib. Learn about RAPIDS cuDF, accelerated data processing, and optimizing machine learning pipelines for enhanced performance and accessibility.

• YouTube
• 21 minutes
• On-Demand
• Free Video

DevConf

GPU Accelerated Containers on Apple Silicon with libkrun and podman machine

Explore GPU-accelerated containers on Apple Silicon using libkrun and podman machine. Learn to run AI workloads efficiently in containers, leveraging macOS hardware for optimal performance.

• YouTube
• 16 minutes
• On-Demand
• Free Video

USENIX

Fast Vector Query Processing for Large Datasets Beyond GPU Memory with Reordered Pipelining

Innovative GPU-accelerated system for efficient vector query processing on large datasets, overcoming memory limitations and outperforming existing solutions in performance and cost-effectiveness.

• YouTube
• 15 minutes
• On-Demand
• Free Video

Databricks

Spark RAPIDS ML - GPU Accelerated Distributed Machine Learning in Spark Clusters

GPU-accelerated machine learning in Spark using RAPIDS ML, offering significant speedup and cost savings over traditional MLlib implementations for large-scale distributed ML applications.

• YouTube
• 38 minutes
• On-Demand
• Free Video

Packt

Advanced Generative Adversarial Networks (GANs)

Master AI-driven image synthesis with GANs. Learn architectures, implement models, and optimize performance using popular datasets. Apply knowledge to generate realistic images for practical applications.

• Coursera
• 12 hours 31 minutes
• On-Demand
• Free Online Course (Audit)

Using GPUs to Scale and Speed-up Deep Learning

1 review

Training complex deep learning models with large datasets takes along time. In this course, you will learn how to use accelerated GPU hardware to overcome the scalability problem in deep learning.

• edX
• 5 weeks, 2-4 hours a week
• On-Demand
• Free Online Course (Audit)

Accelerating Deep Learning with GPUs

Learn to leverage GPU hardware for faster deep learning, deploying networks for image and video classification using platforms like IBM Power AI with NVIDIA GPUs.

• Cognitive Class
• 5 hours
• On-Demand
• Free Online Course

Pragmatic AI Labs

DevOps, DataOps, MLOps

Streamline AI Operations: Leverage DevOps, DataOps, and MLOps for End-to-End Machine Learning Solutions.

• edX
• 4 weeks, 3-6 hours a week
• On-Demand
• Free Online Course (Audit)

Pragmatic AI Labs

Rust for Large Language Model Operations (LLMOps)

Develop efficient Large Language Model solutions using Rust.

• edX
• 4 weeks, 3-6 hours a week
• On-Demand
• Free Online Course (Audit)

Learn to use CUDA C/C++ tools and techniques to accelerate CPU-only applications to run on massively parallel GPUs.

• Independent
• 8 hours
• On-Demand
• $90.00

Microcredential

Deep Learning with IBM

Comprehensive introduction to Deep Learning, covering neural networks, popular frameworks, and GPU acceleration. Hands-on projects prepare learners for real-world AI applications and career opportunities.

• edX
• 31 weeks, 2-4 hours a week
• On-Demand
• $584.00
• 6 courses

Microcredential

Deep Learning

Comprehensive introduction to Deep Learning, covering neural networks, popular frameworks, and GPU acceleration. Hands-on projects prepare learners for real-world AI applications and career opportunities.

• edX
• 26 weeks, 2-4 hours a week
• On-Demand
• $495.00
• 5 courses

Nvidia

Getting Started with Caffe - Deep Learning Framework Introduction - Class 3

Learn to define, train, and deploy Deep Neural Networks using Caffe framework. Covers data management, network definition, training monitoring, and deployment for classification or feature extraction.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Nvidia

Getting Started with OpenACC - Part II

Learn OpenACC for GPU acceleration in scientific computing. Covers data management, parallel kernels, MPI integration, and optimization techniques for high-performance code.

• YouTube
• 30 minutes
• On-Demand
• Free Video