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) and an additional 12 workbooks with extra practice problems, to help you test your understanding along the way. Become a Linear Algebra Master is organized into the following sections:

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) and an additional 12 workbooks with extra practice problems, to help you test your understanding along the way. Become a Linear Algebra Master is organized into the following sections:

  • Operations on one matrix, including solving linear systems, and Gauss-Jordan elimination

  • Operations on two matrices, including matrix multiplication and elimination matrices

  • Matrices as vectors, including linear combinations and span, linear independence, and subspaces

  • Dot products and cross products, including the Cauchy-Schwarz and vector triangle inequalities

  • Matrix-vector products, including the null and column spaces, and solving Ax=b

  • Transformations, including linear transformations, projections, and composition of transformations

  • Inverses, including invertible and singular matrices, and solving systems with inverse matrices

  • Determinants, including upper and lower triangular matrices, and Cramer's rule

  • Transposes, including their determinants, and the null (left null) and column (row) spaces of the transpose

  • Orthogonality and change of basis, including orthogonal complements, projections onto a subspace, least squares, and changing the basis

  • Orthonormal bases and Gram-Schmidt, including definition of the orthonormal basis, and converting to an orthonormal basis with the Gram-Schmidt process

  • Eigenvalues and Eigenvectors, including finding eigenvalues and their associate eigenvectors and eigenspaces, and eigen in three dimensions

AND HERE' We start from the beginning... I explain the problem setup and why I set it up that way, the steps I take and why I take them, how to work through the yucky, fuzzy middle parts, and how to simplify the answer when you get it.

Notes: The notes section of each lesson is where you find the most important things to remember. It’s like Cliff Notes for books, but for math. Everything you need to know to pass your class and nothing you don’t.

Quizzes: When you think you’ve got a good grasp on a topic within a course, you can test your knowledge by taking one of the quizzes. If you pass, great. If not, you can review the videos and notes again or ask for help in the Q&A section.

Workbooks: Want even more practice? When you've finished the section, you can review everything you've learned by working through the bonus workbook. The workbooks include tons of extra practice problems, so they're a great way to solidify what you just learned in that section.

HERE' Provides an academic foundation of linear algebra to prepare for applied or programming-based courses.” - Christopher C.

  • “I have no words to thank Krista for this amazing course, I was really overwhelmed because I had to take a test for a class I couldn't attend and I didn't know anything about linear algebra and surprisingly this course was what I needed, reading the notes before watching the video helped to understand by myself and when I was lost the video content was a great resource, I got a 9 out of 10 in the test, so I highly recommend to take this course, Krista is such a good teacher.” - Alan M.

  • “I started out as a math major in college, and dropped my major during linear algebra. I wish I had this class and this instructor in college. I might have stuck with my major.” - Eric L.

  • “Notes are great, explanations are clear and starting from the beginning. Terrific so far.” - Phil T.

  • “Very clear and has not skipped any steps. If the rest of the course is like this, I will pass my class with no problem.” - Brandon P.

  • “Really well structured and well explained, and there are plenty of exercises to reinforce the knowledge.” - Ashfaque C.

  • YOU'

    I can't wait for you to get started on mastering Linear Algebra.

    - Krista :)

    Enroll now

    Good to know

    Know what's good
    , what to watch for
    , and possible dealbreakers
    Provides an academic foundation of linear algebra to prepare for applied or programming-based courses
    Emphasizes operations on matrices, linear transformations, determinants, and eigenvector and eigenvalue concepts
    Utilizes notes, quizzes, and workbooks to reinforce the course material
    Course includes interactive practice problems and extra practice materials to deepen understanding
    Prior experience with mathematics and linear algebra is helpful for optimal learning
    Provides a strong foundation for students pursuing further studies or careers in linear algebra

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    Activities

    Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Become a Linear Algebra Master with these activities:
    Organize Your Course Materials
    Organize your notes, assignments, and other course materials to improve your retention and study efficiency.
    Show steps
    • Create a system for organizing your notes.
    • File your assignments by topic or due date.
    • Use a binder or digital tool to keep all your materials together.
    Review Matrix Terminology
    Start by reviewing basic terminology associated with matrices. This will help you understand how to represent and manipulate matrices throughout the course.
    Browse courses on Matrix Operations
    Show steps
    • Identify the number of rows and columns in a matrix.
    • Explain the difference between a row vector and a column vector.
    • Define the transpose of a matrix.
    Solve Systems of Linear Equations Practice
    Practice solving systems of linear equations using various methods to reinforce your understanding.
    Browse courses on Linear Equations
    Show steps
    • Solve a system of equations using Gauss-Jordan elimination.
    • Solve a system of equations using Cramer's rule.
    • Solve a system of equations using the inverse of a matrix.
    Four other activities
    Expand to see all activities and additional details
    Show all seven activities
    Learn About Matrix Inverses
    Explore tutorials on matrix inverses to gain a deeper understanding of their properties and applications.
    Show steps
    • Watch a tutorial on finding the inverse of a matrix.
    • Read an article on the applications of matrix inverses.
    • Try implementing a simple matrix inversion algorithm.
    Create a Visual Representation of Eigenvalues
    Create a visual representation of eigenvalues to enhance your comprehension and communicate your understanding.
    Browse courses on Eigenvalues
    Show steps
    • Choose a dataset or matrix that contains eigenvalues.
    • Plot the eigenvalues on a graph or chart.
    • Analyze the distribution and patterns of the eigenvalues.
    Participate in a Linear Algebra Contest
    Challenge yourself by participating in a linear algebra contest to test your understanding and compete with others.
    Browse courses on Linear Algebra
    Show steps
    • Find a linear algebra contest that aligns with your skill level.
    • Register for the contest and prepare thoroughly.
    • Complete the contest and receive feedback on your performance.
    Contribute to an Open-Source Linear Algebra Library
    Contribute to an open-source linear algebra library to gain practical experience and enhance your understanding.
    Browse courses on Linear Algebra
    Show steps
    • Find an open-source linear algebra library that aligns with your interests.
    • Identify an area where you can contribute, such as bug fixes or feature enhancements.
    • Submit a pull request with your changes and receive feedback from the community.

    Career center

    Learners who complete Become a Linear Algebra Master will develop knowledge and skills that may be useful to these careers:
    Data Scientist
    Data Scientists analyze large and complex datasets to extract meaningful insights and patterns. The Become a Linear Algebra Master course provides a strong foundation in linear algebra, which is essential for understanding and applying statistical and machine learning algorithms. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors is particularly relevant to data science, as these concepts are used in a variety of data analysis and modeling techniques.
    Statistician
    Statisticians collect, analyze, and interpret data to provide insights and make predictions. The Become a Linear Algebra Master course provides a solid foundation in linear algebra, which is essential for understanding statistical models and techniques. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors is particularly relevant to statistics, as these concepts are used in a variety of statistical analyses and modeling techniques.
    Machine Learning Engineer
    Machine Learning Engineers design and develop machine learning models to solve complex problems. The Become a Linear Algebra Master course provides a solid foundation in linear algebra, which is essential for understanding and applying machine learning algorithms. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors is particularly relevant to machine learning, as these concepts are used in a variety of machine learning algorithms and techniques.
    Financial Analyst
    Financial Analysts provide financial advice and make investment recommendations to individuals and organizations. The Become a Linear Algebra Master course provides a strong foundation in linear algebra, which is essential for understanding financial models and techniques. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors is particularly relevant to finance, as these concepts are used in a variety of financial models and analyses.
    Actuary
    Actuaries assess and manage financial risk. The Become a Linear Algebra Master course provides a strong foundation in linear algebra, which is essential for understanding and applying actuarial models and techniques. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors is particularly relevant to actuarial science, as these concepts are used in a variety of actuarial models and analyses.
    Operations Research Analyst
    Operations Research Analysts use mathematical and analytical techniques to improve the efficiency and effectiveness of organizations. The Become a Linear Algebra Master course provides a strong foundation in linear algebra, which is essential for understanding and applying operations research models and techniques. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors is particularly relevant to operations research, as these concepts are used in a variety of operations research models and analyses.
    Quantitative Analyst
    Quantitative Analysts use mathematical and statistical models to analyze and predict financial markets. The Become a Linear Algebra Master course provides a strong foundation in linear algebra, which is essential for understanding and applying quantitative finance models and techniques. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors is particularly relevant to quantitative finance, as these concepts are used in a variety of quantitative finance models and analyses.
    Risk Manager
    Risk Managers identify and assess potential risks and develop strategies to mitigate them. The Become a Linear Algebra Master course provides a strong foundation in linear algebra, which is essential for understanding and applying risk management models and techniques. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors is particularly relevant to risk management, as these concepts are used in a variety of risk management models and analyses.
    Software Engineer
    Software Engineers design, develop, and maintain software applications. The Become a Linear Algebra Master course may be useful for Software Engineers who want to develop a deeper understanding of the mathematical foundations of computer science. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors can be helpful for understanding and applying software algorithms and data structures.
    Data Analyst
    Data Analysts clean, analyze, and interpret data to extract meaningful insights. The Become a Linear Algebra Master course may be useful for Data Analysts who want to develop a deeper understanding of the mathematical foundations of data analysis. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors can be helpful for understanding and applying data analysis techniques.
    Business Analyst
    Business Analysts analyze business processes and systems to identify areas for improvement. The Become a Linear Algebra Master course may be useful for Business Analysts who want to develop a deeper understanding of the mathematical foundations of business analysis. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors can be helpful for understanding and applying business analysis techniques.
    Systems Analyst
    Systems Analysts design and implement computer systems to meet the needs of organizations. The Become a Linear Algebra Master course may be useful for Systems Analysts who want to develop a deeper understanding of the mathematical foundations of computer systems. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors can be helpful for understanding and applying systems analysis techniques.
    Computer Scientist
    Computer Scientists research and develop new computer technologies and applications. The Become a Linear Algebra Master course may be useful for Computer Scientists who want to develop a deeper understanding of the mathematical foundations of computer science. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors can be helpful for understanding and applying computer science algorithms and data structures.
    Mathematician
    Mathematicians conduct research in various areas of mathematics. The Become a Linear Algebra Master course may be useful for Mathematicians who want to develop a deeper understanding of linear algebra. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors can be helpful for understanding and applying advanced linear algebra concepts.
    Teacher
    Teachers instruct students in a variety of academic subjects. The Become a Linear Algebra Master course may be useful for Teachers who want to develop a deeper understanding of linear algebra to teach the subject more effectively. The course's coverage of matrix operations, transformations, and eigenvalues and eigenvectors can be helpful for understanding and applying linear algebra concepts in the classroom.

    Reading list

    We've selected 15 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Become a Linear Algebra Master.
    Provides a rigorous and comprehensive introduction to linear algebra, covering topics such as vector spaces, linear transformations, matrices, and eigenvalues and eigenvectors. It valuable reference for students who want to deepen their understanding of the subject.
    Classic textbook on linear algebra that provides a clear and concise introduction to the subject. It covers a wide range of topics, including vector spaces, linear transformations, matrices, and eigenvalues and eigenvectors. It good choice for students who want to learn the basics of linear algebra.
    Popular textbook on linear algebra that provides a balanced approach between theory and applications. It covers a wide range of topics, including vector spaces, linear transformations, matrices, and eigenvalues and eigenvectors. It good choice for students who want to learn the basics of linear algebra and see how it is used in practice.
    Rigorous and comprehensive introduction to linear algebra that is suitable for advanced undergraduates and graduate students. It covers a wide range of topics, including vector spaces, linear transformations, matrices, and eigenvalues and eigenvectors.
    Concise and engaging introduction to linear algebra that emphasizes applications. It covers a wide range of topics, including vector spaces, linear transformations, matrices, and eigenvalues and eigenvectors. It good choice for students who want to learn the basics of linear algebra and see how it is used in practice.
    Modern and engaging introduction to linear algebra that emphasizes applications. It covers a wide range of topics, including vector spaces, linear transformations, matrices, and eigenvalues and eigenvectors.
    Clear and concise introduction to linear algebra that is suitable for beginners. It covers a wide range of topics, including vector spaces, linear transformations, matrices, and eigenvalues and eigenvectors. It good choice for students who want to learn the basics of linear algebra.
    Comprehensive introduction to advanced topics in linear algebra, such as multilinear algebra, tensor algebra, and representation theory. It is suitable for graduate students and researchers who want to learn about these topics.
    Comprehensive introduction to linear algebra and matrix analysis that is specifically designed for students in statistics. It covers a wide range of topics, including vector spaces, linear transformations, matrices, and eigenvalues and eigenvectors. It good choice for students who want to learn the basics of linear algebra and see how it is used in statistics.
    Comprehensive introduction to linear algebra that is specifically designed for students in economics. It covers a wide range of topics, including vector spaces, linear transformations, matrices, and eigenvalues and eigenvectors. It good choice for students who want to learn the basics of linear algebra and see how it is used in economics.
    Comprehensive introduction to applied linear algebra that covers a wide range of topics, including vector spaces, linear transformations, matrices, and eigenvalues and eigenvectors. It good choice for students who want to learn the basics of linear algebra and see how it is used in a variety of applications.
    Comprehensive introduction to matrix theory that is suitable for graduate students and researchers. It covers a wide range of topics, including matrix algebra, matrix functions, and matrix decompositions.
    Comprehensive introduction to tensor analysis on manifolds that is suitable for graduate students and researchers. It covers a wide range of topics, including tensor algebra, differential forms, and Riemannian geometry.
    Comprehensive introduction to algebraic geometry that is suitable for graduate students and researchers. It covers a wide range of topics, including algebraic varieties, schemes, and cohomology.
    Comprehensive introduction to representation theory that is suitable for graduate students and researchers. It covers a wide range of topics, including Lie algebras, representations of Lie groups, and characters.

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