If you're willing to understand how neural networks work behind the scene and debug the back-propagation algorithm step by step by yourself, these slides should be a good starting point.
We will cover deep learning popular applications, the concept of the artificial neuron and how it relates to the biological one, the perceptron and the multi-layer one. We'll also dive in activation functions, loss functions and formalize the training of a neural net via the back-propagation algorithm.
In the last part, you'll learn how to code a fully functioning trainable neural network from scratch. In pure python code only, with no frameworks involved.