Matrix Calculation Course
This course builds strong skills in matrix calculations for practical modeling tasks. Learners review essential linear algebra, create reliable design matrices, and solve linear and logistic regression problems using stable numerical techniques like QR, SVD, Cholesky, and regularization. It emphasizes efficient gradient methods and troubleshooting for professional, reproducible results in mathematics and data work.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain practical mastery in matrix-based modeling through this course. Review key linear algebra concepts, construct and validate design matrices, solve normal equations with or without regularization, apply robust numerical methods, implement matrix forms of logistic and linear regression, and use optimization techniques for dependable outcomes.
Elevify advantages
Develop skills
- Build clean design matrices X and targets y quickly for regression.
- Implement logistic models using matrix forms for sigmoid, loss, and gradients.
- Solve normal equations stably with QR, SVD, and Cholesky methods.
- Identify and fix numeric problems like rank loss using ridge regularization.
- Interpret matrix results including coefficients and effect sizes clearly.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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