Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors
About this Course
This course is the second course in the Linear Algebra Specialization. In this course, we continue to develop the techniques and theory to study matrices as special linear transformations (functions) on vectors. In particular, we develop techniques to manipulate matrices algebraically. This will allow us to better analyze and solve systems of linear equations. Furthermore, the definitions and theorems presented in the course allow use to identify the properties of an invertible matrix, identify relevant subspaces in R^n, We then focus on the geometry of the matrix transformation by studying the eigenvalues and eigenvectors of matrices. These numbers are useful for both pure and applied concepts in mathematics, data science, machine learning, artificial intelligence, and dynamical systems. We will see an application of Markov Chains and the Google PageRank Algorithm at the end of the course.Created by: Johns Hopkins University
Related Online Courses
In this course, you will learn how to make strategic decisions quickly and effectively in uncertain and complex environments. You will explore frameworks and tools that enable faster... more
In this 1-hour long project-based course, you will learn how to compare the performance of different securities using financial statistics (normal distributions) and the Google Sheets toolkit to... more
Python is one of the most popular and widely-used programming languages in the world, due to its high usability and large collection of libraries. This learning path provides an application-driven... more
Perfect markets achieve efficiency: maximizing total surplus generated. But real markets are imperfect. In this course we will explore a set of market imperfections to understand why they fail and... more
This specialization is intended for beginners to learn how to become proficient in Linux programming. It will prepare you for a role as an information technology professional by introducing you to... more