
Overview
Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data.
The programme
Discover the Singular Value Decomposition with this Matrix Methods offered by Coursera in partnership with University of Minnesota that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction. Optional examples using Python are used to illustrate the concepts and allow the learner to experiment with the algorithms.
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Visit university websiteProgramme Structure
Courses include:
- Matrices as Mathematical Objects
- Matrix Multiplication and other Operations
- Systems of Linear Equations
- Linear Least Squares
- Singular Value Decomposition
Check out the full curriculum
Visit university websiteKey information
Duration
- Part-time
- 1 months
Start dates & application deadlines
Language
Delivered
Disciplines
Mathematics Applied Mathematics Machine Learning View 256 other Short Courses in Machine Learning in United StatesExplore more key information
Visit university websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Intermediate Level
Make sure you meet all requirements
Visit university websiteTuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months.
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Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved.