- Statistical Methods
- Applied Mathematics
- Data Analysis
- Linear Algebra
- Data Science
- Algebra
- Numerical Analysis
Essential Linear Algebra for Data Science
Completed by Alex Michael Heilman
October 3, 2022
7 hours (approximately)
Alex Michael Heilman's account is verified. Coursera certifies their successful completion of Essential Linear Algebra for Data Science
What you will learn
Solve real-world problems using the foundational concept of matrices and explain where those problems might arise.
Recognize what a matrix represents in n-dimensional space and how transformations act in that space
Identify key properties of any system of equations, such as independence, basis, rank, and more, and what they mean for the overall system.
Demonstrate your understanding of projections in lower dimensions, while being able to carry out higher dimension projections for real-world problems
Skills you will gain
