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Class Schedule

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Note: this course schedule is tentative and subject to change.

Overview

We focus on the slice of Python that powers scientific computing and data science. Plan on eight fast-paced lectures; links below point to the live Colab notebooks so you can follow along during class or review afterward. Expect minor adjustments as the quarter progresses—check back for updates.

Lecture Schedule and Outline

  • Week 1 (Wednesday, 09/24): Python Basics Lecture Notes: Lecture 1 Notebook
  • Week 2 (Wednesday, 10/01): Object-Oriented Programming in Python Lecture Notes: Lecture 2 Notebook
  • Week 3 (Wednesday, 10/08): Introduction to Python Arrays with NumPy and PyTorch Lecture Notes: Lecture 3 Notebook
  • Week 4 (Wednesday, 10/15): Data Management and Manipulation with Pandas** Lecture Notes: Lecture 4 Notebook
  • Week 5 (Wednesday, 10/22): Introduction to Visualization with Matplotlib and Seaborn Lecture Notes: Lecture 5 Notebook
  • Week 6 (Wednesday, 10/29): Introduction to statistical modeling with scikit-learn Lecture Notes: Colab notebook (to be added)
  • Week 7 (Wednesday, 11/05): Advanced machine learning with scikit-learn Lecture Notes: Colab notebook (to be added) Additional Resource: Hands-on Machine Learning companion notebooks (to be added)
  • Week 8 (Wednesday, 11/12): Deep Learning with PyTorch Lecture Notes: Colab notebook (to be added) Supplement: Neural network slides (to be added)
  • Week 9 (Wednesday, 11/19): Introduction to Hugging Face Transformers Lecture Notes: Colab notebook (to be added)
  • Week 10 (Wednesday, 11/26): Thanksgiving Break, No Class.
  • Week 11 (Wednesday, 12/03): End of Quarter Period, No Class.

Historical Archives

Looking for earlier iterations? Browse snapshots that preserve prior term content: Spring 2025