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!

This course is part of the Linear Algebra for Data Science Using Python Specialization

Offered By

## About this Course

## Offered by

### Howard University

Founded in 1867, Howard University is a private, research university that is comprised of 14 schools and colleges. Students pursue more than 140 programs of study leading to undergraduate, graduate and professional degrees. The University operates with a commitment to Excellence in Truth and Service and has produced one Schwarzman Scholar, three Marshall Scholars, four Rhodes Scholars, 12 Truman Scholars, 25 Pickering Fellows and more than 165 Fulbright recipients. Howard also produces more on-campus African American Ph.D. recipients than any other university in the United States. For more information on Howard University, visit www.howard.edu.

## Syllabus - What you will learn from this course

**2 hours to complete**

## Introduction to finding inverses

In module 1, youâ€™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.

**2 hours to complete**

**2 hours to complete**

## Introduction to Matrix Algebra with Python

Letâ€™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, youâ€™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.

**2 hours to complete**

**2 hours to complete**

## Solving Systems of Linear Equations

Letâ€™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.

**2 hours to complete**

**4 hours to complete**

## 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, youâ€™ll apply what youâ€™ve learned to concrete, real-world examples. Youâ€™ll practice using linear transformation, Eigenvalues and Eigenvectors, and solving applications. We will cover the following learning objectives.

**4 hours to complete**

## About the Linear Algebra for Data Science Using Python Specialization

This Specialization is for learners interested in exploring or pursuing careers in data science or understanding some data science for their current roles. This course will build upon your previous mathematical foundations and equip you with key applied tools for using and analyzing large data sets.

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