Coursera
Dive into the world of deep learning and master the powerful PyTorch framework with our expert-led course. From understanding basic concepts like tensors and automatic differentiation, to implementing complex models such as convolutional networks and recurrent neural networks, you'll gain a thorough understanding of building state-of-the-art deep learning solutions.
EdX
Embark on a journey into the world of embedded systems with our comprehensive Computer Vision for Embedded Systems course. Designed for those looking to harness the power of computer vision within constrained environments, this course will guide you through the intricacies of running advanced algorithms such as OpenCV and PyTorch on devices like Raspberry Pi and NVIDIA Jetson. Master the art of optimizing performance and minimizing resource consumption while unlocking new possibilities in your projects.
Udacity
Dive into the world of deep learning with Udacity's 'Intro to Deep Learning with PyTorch'. Learn the basics of deep learning and implement your first deep neural network using PyTorch. Gain hands-on experience through coding exercises and projects that cover cutting-edge AI applications like style transfer and text generation.
Manning Publications
Dive into 'Getting Started with Google Colab Using PyTorch' and master the art of cloud-based machine learning. This course is designed for beginners and intermediate learners who want to harness the power of Google Colab for data science projects, specifically using PyTorch for deep learning tasks. You'll gain hands-on experience in preprocessing data, taking advantage of free GPU/TPU resources, and building classifiers with scikit-learn and PyTorch.
Udacity
Embark on a journey into the future of secure and private AI with this comprehensive online course from Udacity. Gain expertise in privacy-preserving technologies such as Federated Learning, Differential Privacy, and Encrypted Computation. Master these techniques using PyTorch extensions like PySyft to train models safely and securely on distributed private data.