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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 2023): Aaditya Prakash Kattekola, Arghavan Zibaie, Zihu Wang, Jesse Lee, Karthik Somayaji Nanjangud Suryanarayana, Yuxuan Yin.

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 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.

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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