Build a neural network from scratch without using any ML frameworks. Implement forward propagation, backpropagation, and gradient descent to understand the fundamentals of how deep learning works at the mathematical level.
Stripping away the abstractions of popular frameworks forces you to engage directly with the linear algebra and calculus that power modern AI systems.