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Course Description

To perform basic computations in the Machine Learning certificate program, you need the ability to solve elementary linear algebra problems in two dimensions. In this course, you will execute mathematical computations on vectors and measure the distance from a vector to a line. This course will provide you with the theory and activities to start building the linear algebra foundation needed to be successful in your Machine Learning courses.

This optional self-paced course supports the required linear algebra in the Machine Learning certificate. If you are already comfortable with the computations from the pretest, we recommend that you take the final assessment to confirm your readiness.

Faculty Author

Kilian Weinberger

Benefits to the Learner

  • Write a vector and a matrix
  • Test whether two vectors are orthogonal using the dot product
  • Define a plane in space
  • Compute distance to a plane in a low dimension

Target Audience

  • Programmers
  • Developers
  • Data analysts
  • Statisticians
  • Data scientists
  • Software engineers
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Type
self-paced (non-instructor led)
Dates
Mar 25, 2020 to Dec 31, 2025
Course Fee(s)
Standard Price $0.00
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