This text focuses on the primary topics in a first course in Linear Algebra. The author includes additional advanced topics related to data analysis, singular value decomposition, and connections to differential equations. This is a lab text that would lead a class through Linear Algebra using Mathematica® demonstrations and Mathematica® coding.

The book includes interesting examples embedded in the projects. Examples include the discussions of “Lights Out”, Nim, the Hill Cipher, and a variety of relevant data science projects.

The 2nd Edition contains:

• Additional Theorems and Problems for students to prove/disprove (these act as theory exercises at the end of most sections of the text)
• Additional sections that support Data Analytics techniques, such as Kronecker sums and products, and LU decomposition of the Vandermonde matrix
• Updated and expanded end-of-chapter projects

Instructors and students alike have enjoyed this popular book, as it offers the opportunity to add Mathematica® to the Linear Algebra course.

I would definitely use the book (specifically the projects at the end of each section) to motivate undergraduate research.—Nick Luke, North Carolina A&T State University.

This text focuses on the primary topics in a first course in Linear Algebra. The author includes additional advanced topics related to data analysis, singular value decomposition, and connections to differential equations. This is a lab text that would lead a class through Linear Algebra using Mathematica® demonstrations and Mathematica® coding.

The book includes interesting examples embedded in the projects. Examples include the discussions of “Lights Out”, Nim, the Hill Cipher, and a variety of relevant data science projects.

The 2nd Edition contains:

• Additional Theorems and Problems for students to prove/disprove (these act as theory exercises at the end of most sections of the text)
• Additional sections that support Data Analytics techniques, such as Kronecker sums and products, and LU decomposition of the Vandermonde matrix
• Updated and expanded end-of-chapter projects

Instructors and students alike have enjoyed this popular book, as it offers the opportunity to add Mathematica® to the Linear Algebra course.

I would definitely use the book (specifically the projects at the end of each section) to motivate undergraduate research.—Nick Luke, North Carolina A&T State University.

This text focuses on the primary topics in a first course in Linear Algebra. The author includes additional advanced topics related to data analysis, singular value decomposition, and connections to differential equations. This is a lab text that would lead a class through Linear Algebra using Mathematica® demonstrations and Mathematica® coding.

The book includes interesting examples embedded in the projects. Examples include the discussions of “Lights Out”, Nim, the Hill Cipher, and a variety of relevant data science projects.

The 2nd Edition contains:

• Additional Theorems and Problems for students to prove/disprove (these act as theory exercises at the end of most sections of the text)
• Additional sections that support Data Analytics techniques, such as Kronecker sums and products, and LU decomposition of the Vandermonde matrix
• Updated and expanded end-of-chapter projects

Instructors and students alike have enjoyed this popular book, as it offers the opportunity to add Mathematica® to the Linear Algebra course.

I would definitely use the book (specifically the projects at the end of each section) to motivate undergraduate research.—Nick Luke, North Carolina A&T State University.