1. Learn some calculus. Especially on how to find partial derivatives. The core of neural network training is finding the partial derivative for each weight and bias. 3blue1brown has an amazing calculus playlist on calculus.
2. Learn some linear algebra. Especially on how matrices work.
3. Learn how to use numpy, a python library for manipulating n-dimension arrays. It's essential for machine learning projects in Python.
   
4. Watch 3blue1brown's But what is a Neural Network? for an intuitive understanding of a neural network.
5. Implement your own neural network from scratch (with back propagation). Find a youtube video or guide to help on the internet.

See you in a few months.