Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors
This course is part of Linear Algebra from Elementary to Advanced.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Linear Algebra from Elementary to Advanced Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Understand matrix operations and inverse matrices
Master determinant calculations and their applications
Analyze eigenvalues and eigenvectors of matrices
Study matrix diagonalization and its implications
Apply concepts to Markov Chains and PageRank algorithm
Skills you'll gain
This course includes:
3.8 Hours PreRecorded video
18 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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Get a Completion Certificate
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There are 6 modules in this course
This advanced course explores matrix algebra, determinants, and eigenvectors as tools for understanding linear transformations. Students learn to manipulate matrices algebraically, analyze invertible matrices, and study subspaces in R^n. The curriculum covers eigenvalues and eigenvectors, with applications to Markov Chains and the Google PageRank Algorithm. Through theoretical understanding and practical examples, students develop skills essential for advanced mathematics, data science, machine learning, and dynamical systems.
Matrix Algebra
Module 1 · 2 Hours to complete
Subspaces
Module 2 · 2 Hours to complete
Determinants
Module 3 · 3 Hours to complete
Eigenvectors and Eigenvalues
Module 4 · 2 Hours to complete
Diagonalization and Linear Transformations
Module 5 · 2 Hours to complete
Final Assessment
Module 6 · 1 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Linear Algebra from Elementary to Advanced
Instructor
Associate Teaching Professor and Director of Online Programs at Johns Hopkins University
Dr. Joseph W. Cutrone is an Associate Teaching Professor and the Director of Online Programs at Johns Hopkins University, where he specializes in mathematics education. He earned his PhD in Mathematics from Johns Hopkins University, with research interests focused on higher-dimensional algebraic geometry. Since 2006, Dr. Cutrone has taught mathematics at various levels, both online and in traditional classroom settings, holding positions at Johns Hopkins, Northwestern University, Towson University, and Goucher College. His commitment to education is reflected in his extensive teaching portfolio, which includes courses such as Algebra, Applied Calculus with Python, and Linear Algebra. Dr. Cutrone is also active in online education, contributing to platforms like Coursera. His scholarly work includes several publications on topics related to algebraic geometry and has been recognized for its impact within the mathematical community.
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