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Repository Details

Pilot course for Robotics 101: Computational Linear Algebra

Robotics 101: Computational Linear Algebra

Computational Linear Algebra is a first-semester, first-year undergraduate course that shows how mathematics and computation are unified for reasoning about data and making discoveries about the world.

The first iteration of the course ran in Fall 2020 at the University of Michigan Robotics Institute.

Linear algebra and coding are rapidly becoming an essential foundation for the modern engineer in a computational world. Students in this course will gain insights into the mathematical theory of linear algebra and its realization in practical computational tools.

Math is the language of engineering, but coding is believing and realizing it. The mathematical content of ROB 101 is built around systems of linear equations, their representation as matrices, and numerical methods for their analysis. These methods will be given life through the lens of robotics and contemporary intelligent systems and their compelling applications.

The entire course is available for the terms:

And the homework and projects:

Lecture, Recitation, and Lab Videos

All lecture, recitation, and lab videos are available on YouTube:

Lecture notes as well as recitation notes are also available in the repository.

Textbook

The textbook, Notes for Computational Linear Algebra, continues to be updated, and it is now available in LaTeX format in it's own GitHub repository.

Projects

Three main projects that accompany the course are available in the repository.

Course Plan

Course plans for each term are in their respective repositories. Please let us know if anything is unclear.

Course Evaluation

Students thoughts on the courses can be read in the teaching evaluations.

Credits

  • Chad Jenkins, Associate Director of Undergraduate Programs, Michigan Robotics
  • Jessy Grizzle, Director, Michigan Robotics
  • Maani Ghaffari, Assistant Professor, Naval and Marine Architecture, U-M
  • Kira Biener
  • Tribhi Kathuria
  • John Pye
  • Madhav Achar
  • Fangtong (Miley) Liu
  • Shaoxiong Yao
  • Eva Mungai
  • Bruce JK Huang
  • Grant A. Gibson
  • Oluwami Dosunmu-Ogunbi
  • Lu Gan
  • Ray Zhang

License

All code is licensed under the GNU General Public License v3.0.

All other content, including textbooks, homeworks, and video, is licensed under the Creative Commons Attribution-NonCommericial 4.0 (CC BY-NC 4.0).

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