Learning Path

Python Programming (Intermediate) → Debugging and Profiling PyTorch Models

This advanced learning path equips deep learning practitioners with the skills to implement, train, and evaluate deep learning models using PyTorch. It covers essential PyTorch components—tensors, autograd, neural network modules, data loading, and training loops—and extends to advanced architectures like CNNs, RNNs, and Transformers. The path integrates necessary machine learning and Python prerequisites, ensuring a solid foundation for practical implementation.