Syllabus

This is a course on scientific computing using Python. We'll cover aspects of the Python language as they are relevant to the material. The following schedule should be seen as a high-level guide to what we'll do in 8 lectures, but is not set in stone. Please check regularly, as lectures are added as we progress.

1. Python basics
   • pre-lecture: [colab]
2. Python Classes and Objects
   • pre-lecture: [colab] [Code for Exercise 1]
3. Introduction to Numpy
   • pre-lecture: [colab]
4. Linear Algebra with Numpy
   • pre-lecture: [colab]
5. Introduction to Scipy
   • pre-lecture: [colab]
6. Introduction to Pandas
7. Introduction to Scikit-learn
8. Deep Learning with PyTorch

Content from previous offerings of the course:

• Winter 2019-2020
• Fall 2019-2020