CUDA Courses and Certifications

Coursera

OpenCL Programming

Master OpenCL programming for parallel computing across CPUs, GPUs, and FPGAs. Develop high-performance applications, optimize kernels, manage memory efficiently, and scale computations for AI, scientific simulations, and more.

• Coursera
• 3 hours 41 minutes
• Self-Paced
• Paid Course

Packt

Deep Learning - Computer Vision for Beginners Using PyTorch

Master PyTorch and deep learning for computer vision. Build neural networks, implement CNNs, and apply skills to real-world datasets. Includes optional Python basics and data science libraries.

• Coursera
• 9 hours 40 minutes
• Self-Paced
• Paid Course

Coursera Career Certificate

Blueprint to Bytecode: Architecting Scalable AI Systems

Master the full AI systems lifecycle—from data pipelines and GPU clusters to cloud deployment—using Kubernetes, Docker, SageMaker, and MLOps best practices to build scalable, production-ready enterprise AI solutions.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 10 courses

Birla Institute Of Technology And Science–Pilani (BITS–Pilani)

Multicore and GPGPU Programming

Master parallel programming with multicore CPUs and GPUs, covering CUDA, Pthreads, MPI, and OpenMP to build high-performance, multi-threaded applications with optimised resource utilisation.

• Coursera
• 56 hours
• Self-Paced
• Paid Course

A+ Core 1 V15 - Pearson Cert Prep: Unit 3

Master PC hardware fundamentals including CPUs, motherboards, RAM, storage, power supplies, and SOHO devices with hands-on procedures for A+ certification success.

• Coursera
• 11 hours 23 minutes
• Self-Paced
• Paid Course

Coursera

GPU Clusters & Containers

Unlock distributed AI training and production deployment using cloud GPU clusters and containerization strategies for scalable machine learning systems.

• Coursera
• 2 hours 5 minutes
• Self-Paced
• Paid Course

AI Infrastructure: Networking Techniques

Master Google Cloud's high-bandwidth, low-latency networking to optimize AI workloads from data ingestion through training to inference, maximizing computational performance.

• Coursera
• 3 hours 56 minutes
• Self-Paced
• Paid Course

Deploy and Scale AI Models with Cloud Run

Discover how to deploy and optimize AI inference services on Cloud Run with GPU support and data storage integration for efficient serverless ML applications.

• Coursera
• 1 hour 24 minutes
• Self-Paced
• Paid Course

EDUCBA

Design Scalable OpenGL Rendering Architectures

Master modular OpenGL rendering systems with shader communication, vertex data structuring, buffer abstractions, and scalable renderer architectures for professional graphics programming.

• Coursera
• 8 hours 22 minutes
• Self-Paced
• Paid Course

Pragmatic AI Labs

GitHub: Codespaces, Actions, and Ecosystem Tools

Master cloud-based dev environments with GitHub Codespaces, GPU-accelerated AI workloads, Copilot-assisted coding, and automated CI/CD pipelines using GitHub Actions.

• Coursera
• 2 hours 38 minutes
• Self-Paced
• Paid Course

Coursera

Automate Cloud Workflows with Python Scripting

Master cloud automation by writing Python scripts that eliminate manual tasks, provision resources, and manage ML workflows with Infrastructure as Code principles.

• Coursera
• 1 hour 25 minutes
• Self-Paced
• Paid Course

KodeKloud

ML Model Development and Tracking: Hands-on Guide

Master MLOps "Middle Loop" with MLflow tracking, model versioning, and production deployment through hands-on insurance claim automation project.

• Coursera
• 3 hours 3 minutes
• Self-Paced
• Paid Course

AI Infrastructure: Deployment Types

Explore Google Cloud's AI infrastructure deployment strategies, from Compute Engine to Kubernetes, with hands-on cluster creation and inference optimization techniques.

• Coursera
• 5 hours 11 minutes
• Self-Paced
• Paid Course

Coursera

Scale Kubernetes: Optimize Your Systems

Master advanced Kubernetes resource optimization for ML/AI workloads through HPA configuration, utilization analysis, and cost-effective scaling strategies in production environments.

• Coursera
• 1 hour 50 minutes
• Self-Paced
• Paid Course

Coursera

Deploy and Optimize Cloud AI Architectures

Master scalable ML deployment on Amazon SageMaker with distributed training, Spot Instances, autoscaling, and cost optimization through GPU monitoring and CloudWatch metrics.

• Coursera
• 1 hour 48 minutes
• Self-Paced
• Paid Course