मुफ्त ऑनलाइन कोर्स Practical PyTorch Deep Learning: Tensors, Autograd, CNNs, RNNs, Transfer Learning and Optuna

कोर्स का विवरण

Practical PyTorch Deep Learning is a free online course designed to help you build real deep learning skills with PyTorch, from the first tensor operation to training modern neural networks end to end. It guides you through the core building blocks of the framework so you can move confidently from experimentation to structured model development.

You will learn how tensors work, how automatic differentiation powers learning, and how to assemble a reliable training workflow with the neural network module, datasets, and optimization strategies. The course also covers training on GPU to speed up experiments and improve productivity when iterating on models.

As you progress, you will apply PyTorch to key deep learning architectures used in computer vision and natural language processing. You will explore convolutional neural networks for image tasks, transfer learning to reuse strong pretrained models efficiently, and recurrent networks including LSTM for sequence modeling. Practical NLP applications such as question answering and next word prediction are included to reinforce concepts with hands-on outcomes.

To round out the workflow, the course introduces hyperparameter tuning with Optuna, helping you systematically improve model performance through automated search and better experiment management. Ideal for learners in Artificial Intelligence and Data Science, this course provides a practical path to building, training, and tuning neural networks with PyTorch.