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Learn GPU Computing, earn certificates with free online courses from Stanford, Johns Hopkins, Duke, IIT Kharagpur and other top universities around the world. Read reviews to decide if a class is right for you.
Acelera el entrenamiento de modelos y la ingenierÃa de caracterÃsticas utilizando GPU con CuML y CuDF para optimizar tus flujos de trabajo de aprendizaje automático.
Learn how to get a GPU server online suitable for deep learning— to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems.
Learn parallel programming with CUDA to process large datasets using GPUs. Explore thread management, memory types, and performance optimization techniques for complex problem-solving on Nvidia hardware.
Gain hands-on experience deploying open-source LLMs, from understanding fundamentals to fine-tuning models and building AI applications using a code-first approach.
Explore AI fundamentals, infrastructure, and operations for enterprise professionals. Gain insights into GPU computing, data center design, cloud deployment, and MLOps for effective AI implementation.
Learrn to Code with CUDA with GPGPU-Simulators & Docker, Kickstart Your Computing and Data Science Career!
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.
Learn PyTorch for deep learning: tensors, gradient descent, linear regression, image processing, neural networks, CNNs, ResNet, regularization, data augmentation, and GANs for image generation.
Explore the basics of deep learning using PyTorch and test your knowledge with hands-on challenges.
Discover how to implement transfer learning using PyTorch, the popular machine learning framework.
Comprehensive exploration of GPU architectures and programming, covering CUDA and OpenCL, with focus on optimization techniques and practical applications in modern computing scenarios.
Master high-performance computing through parallel programming, covering MPI, OpenMP, GPU tools, and practical applications in scientific computing. Learn optimization techniques and implement real-world HPC projects.
Learn how you can make the most effective use of deployment, distribution, and licensing for your instance of GitHub Enterprise Administration.
Master high-performance computing fundamentals, parallel programming with OpenMP and MPI, GPU computing, and scientific visualization tools for advanced computational research and simulation applications.
In this course you will learn how to set up a GPU Server on your own infrastructure, download open source models, and build applications with those models programmatically and with Agents
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