In this course, you'll be introduced to finding inverses and matrix algebra using Python. You will also practice using row reduction to solve linear equations as well as practice how to define linear transformations. Let's get started!
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Course 2 of 4 in the Linear Algebra for Data Science Using Python Specialization.
Syllabus
WEEK 1
Introduction to finding inverses
In module 1, you’ll learn how to define linear equations, how to use Python to find the determinant of matrices and how to perform different commands using Python. We will cover the following learning objectives.
WEEK 2
Introduction to Matrix Algebra with Python
Let’s recap! In module 1, you learned how to define linear equations, how to use Python to find the determinant of matrices and how to perform different commands using Python. In module 2, you’ll learn how to explain different matrix algebra functions, perform matrix algebra on large data sets using Python. We will cover the following learning objectives.
WEEK 3
Solving Systems of Linear Equations
Let’s recap! In module 2, you learned how to explain different matrix algebra functions and perform matrix algebra on large data sets using Python. In module 3, you will learn how to solve systems of linear equations using several methods. We will cover the following learning objectives.
WEEK 4
Eigenvalues and Eigenvectors
Welcome to the final module of this course! Over the past 3 modules, you have been introduced to and gained knowledge on the following topics: determinants, inverses, matrix algebra with Python, row reduction and, systems of linear equations. In the final module of the course, you’ll apply what you’ve learned to concrete, real-world examples. You’ll practice using linear transformation, Eigenvalues and Eigenvectors, and solving applications. We will cover the following learning objectives.
