- Learners build simple neural networks using PyTorch.
- Exercises include tasks such as training, evaluating, and optimizing models.
- Realistic datasets are used to simulate practical applications.
- Step-by-step labs reinforce understanding of layers, activation functions, and loss computation.
- Hands-on practice prepares learners for more advanced deep learning courses.
