Although you can understand the lecture notes without knowing Python. I highly recommend to learn and use it, for several reasons:

1. “To get your hands dirty” is necessary for data science. While a concept or a method looks easy to understand, you might miss some important but not so obvious details. A good practice is to try to implement the concept or method by yourself, even it’s simple concept or method. A programming language like Python is the best tool to do this.
2. To realize your idea. During the lectures, you might have some novel idea. Programming language like Python gives you the power to realize the idea, or at least to realize the prototype of it.
3. To do data science beyond this class. I always said this class is just a staring point. If you are interested in data science related research, there is a long way to go. Mastering a programming language is then a basic skill you need.

A common question is that why Python? I think the choice of programming language is quite subjective and even personal. But there are reasons why Python is so popular, especially for data science. First of all, Python is powerful but easy to use, compared with C++. Secondly, Python has plenty libs and frameworks for data analysis and modeling (e.g., Numpy, Pandas, Pytorch, etc.). Thirdly, Python has a large developer community, so you can get the help from the Internet easily.

If you have never used any programming language before, here are some tutorials to start learning Python:

1. W3School python tutorial
2. Programiz python tutorial

And below is an official (but lengthy) tutorial of Python:

https://docs.python.org/3/tutorial/7

If you’ve learned some other programming language, you can read this doc for moving to Python.

Learning a programming language needs practice, we prepared an online programming course of python in Mo:

You need to register an account and go to "training course" to find "Python tutorial", or directly access this link: https://momodel.cn/classroom/class?id=5d1f3ab81afd940ab7d298bf&type=notebook

And after you go into the notebook environment, you can following the tutorial and do programming exercises in your browser. The environment is based on Jupyter Notebook, which is a web-based IDE for Python.