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The lectures present concepts from linear algebra, such as matrix computations, systems of linear equations, eigenspace decomposition, inner-product, orthogonality, least-squares and linear regression. Students actively engage with the materials with an introduction to Python programming

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ECE-3: Python Programming for Science & Engineering

Welcome!

This is the GitHub repository for the course:

ECE-3: Python Programming for Science & Engineering.

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Teaching team

From the Geometric Intelligence Lab:

TAs (Fall 2025): Priyanka Nagasamudra, Bariscan Kurtkaya, Mazdak Mohseni-Rajaee

Interact with the course contents

You can access and run the lecture slides and lab notebooks by clicking on the Binder link below.

Binder

Outline

  • Unit 01: Welcome to Python
  • Unit 02: Computing with Data in Python
  • Unit 03: Summarizing and Visualizing Data in Python
  • Unit 04: Predicting from Data with Machine Learning in Python

Textbooks

The content of this class relies on the following excellent textbooks:

The textbooks are freely available online.

Syllabus

More details are on the syllabus.

Run the jupyter notebook slides

In your terminal:

conda env create -f environment.yml
python -m ipykernel install --user --name=ece3 --display-name "Python (ece3)"
jupyter notebook

Then open the slides of interest, and click Enter/Exit Rise Slideshow Icon.

Best wishes for the new quarter! ☺

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The lectures present concepts from linear algebra, such as matrix computations, systems of linear equations, eigenspace decomposition, inner-product, orthogonality, least-squares and linear regression. Students actively engage with the materials with an introduction to Python programming

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