In this course you will learn how to build neural networks with plain Python. Without the need for any library, you will see how a simple neural network from 4 lines of code, evolves in a network that is able to recognise handwritten digits. In this process, you will learn concepts like: Feed forward, Cost, Back propagation, Hidden layers, Linear regression, Gradient descent and Matrix multiplication.
After this course, you understand how neural networks really work. You have learned how to write the code to create neural networks from the ground up. You have learned the purpose of network parameters and can also use this knowledge if you decide to use a framework like PyTorch or Tensorflow later.
You have some programming experience and an interest in neural networks.