According to Andrew Ng (@AndrewYNg), DeepLearning.AI has launched the PyTorch for Deep Learning Professional Certificate taught by Laurence Moroney (@lmoroney). This three-course program covers core PyTorch fundamentals, advanced neural architectures, and deployment strategies, making it an essential resource for AI professionals and researchers. The curriculum starts with PyTorch basics like tensors and neural network training, advances to hyperparameter tuning and transfer learning with TorchVision and Hugging Face, and culminates with deployment techniques using ONNX and MLflow. The certificate addresses practical business needs by teaching skills such as model optimization, transformer implementation, and diffusion model development, which are critical for building scalable AI systems and custom solutions. This specialization meets high industry demand for PyTorch expertise, offering actionable knowledge for deploying efficient AI models in production environments (Source: @AndrewYNg, DeepLearning.AI, 2025-10-29).

According to DeepLearning.AI (@DeepLearningAI), the new PyTorch for Deep Learning Professional Certificate, led by Laurence Moroney, provides in-depth, practical training on building, optimizing, and deploying deep learning systems using PyTorch—the leading deep learning framework in the AI industry (source: DeepLearning.AI, Twitter, Oct 29, 2025). The program comprises three specialized courses covering fundamentals, advanced architectures like ResNets and Transformers, and deployment techniques with ONNX, MLflow, pruning, and quantization. Participants gain hands-on experience with image classification, model fine-tuning, computer vision, NLP, and deployment workflows, equipping AI professionals and businesses with up-to-date skills for real-world AI applications and scalable model deployment. This certificate directly addresses the growing market demand for PyTorch expertise and deployment-ready AI talent.