Welcome to MSDS-534! Here we will share computing resources for the class.

1. Install Python and get started with environments (guide).
2. Download VSCode (download here)
3. Download Lecture 1 and open it in VSCode
4. To use your msds534 environment, on the top right hand corner, click "Select Kernel" > "Python Environments" > msds534. If it prompts you to install ipykernel, follow the prompts to install it.
5. See if you can run Lecture 1!

• PyCharm (download here -- scroll down for free Community Edition). Note there is no Jupyter notebook (.ipynb files) in community PyCharm.

A good introduction to Python for data science is from Introduction to Statistical Learning, (James, G., Witten, D., Hastie, T., and Tibshirani, R.)

• https://github.com/intro-stat-learning/ISLP_labs/blob/stable/Ch02-statlearn-lab.ipynb

Here is a nice blogpost about learning Python as an R user:

• https://www.rebeccabarter.com/blog/2023-09-11-from_r_to_python

This is a nice introduction to PyTorch -- it starts with a basic linear model and shows you how to code it up in PyTorch (saving the bells and whistles of neural networks for another time)

• https://towardsdatascience.com/understanding-pytorch-with-an-example-a-step-by-step-tutorial-81fc5f8c4e8e

Here we will post Jupyter Notebooks from the lectures.

• Lecture 1
• Lecture 2
• Lecture 3

• Using github