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Mat Leonard, Andrew Paster, Jennifer Staab, Luis Serrano, Juan Delgado, Juno Lee, Mike Yi, Grant Sanderson, and Ortal Arel
Learn the basics of the beautiful world of Linear Algebra and why it is such an important mathematical tool in the world of AI.

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What's inside

Syllabus

Take a sneak peek into the beautiful world of Linear Algebra and learn why it is such an important mathematical tool.
Learn about vectors, the basic building block of Linear Algebra.
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Learn how to scale and add vectors and how to visualize the process.
What is a linear transformation and how is it directly related to matrices? Learn how to apply the math and visualize the concept.
Learn how to graph 2D vectors.
Learn how to computationally determine a vector's span and solve a simple system of equations.
Learn how to solve some problems computationally using vectors and matrices.
Take a peek into the world of Neural Networks and see how it related directly to Linear Algebra!

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Ideal for those unfamiliar with this math
Enhances a basis for those familiar with linear algebra
Instructors are industry professionals

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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 Linear Algebra Essentials with these activities:
Review Matrix Algebra
Review the basics of Matrix Algebra to ensure a solid foundation before beginning this course.
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  • Revisit theorems and proofs about matrix properties.
  • Practice matrix transformation and inversion.
  • Solve systems of equations using matrices.
Review 'Linear Algebra and its Applications' by David C. Lay
Read or revisit key chapters from this classic textbook to solidify your understanding of linear algebra concepts.
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  • Review the chapter on vector spaces and subspaces.
  • Study the chapter on linear transformations and their applications.
Interactive Linear Algebra Simulations
Explore interactive simulations to visualize concepts like vector spaces and transformations.
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  • Use simulations to understand vector addition and scalar multiplication.
  • Visualize the effects of linear transformations on vectors.
Four other activities
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Show all seven activities
Matrix Operations Drills
Sharpen your skills in performing matrix operations and solving matrix equations.
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  • Practice finding determinants and inverses of matrices.
  • Solve systems of linear equations using matrices.
Explain Linear Transformations to a Classmate
Deepen your understanding by explaining the concept of linear transformations to someone else.
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  • Prepare a clear and concise explanation of linear transformations.
  • Find a classmate and present your explanation to them.
  • Answer any questions and engage in a discussion about linear transformations.
Collaborative Problem-Solving Session
Team up with peers to solve challenging linear algebra problems together.
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  • Form a study group with classmates who have similar interests in linear algebra.
  • Choose a set of problems from the course or a textbook.
  • Work together to solve the problems, discussing different approaches and strategies.
Develop a Linear Algebra Toolkit
Create a comprehensive resource that summarizes key concepts and provides practical tools for applying linear algebra.
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  • Gather notes, resources, and examples related to linear algebra.
  • Organize and structure the material into a cohesive toolkit.
  • Include clear explanations, step-by-step examples, and useful formulas.

Career center

Learners who complete Linear Algebra Essentials will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists explore large sets of data to draw meaningful conclusions that drive business decisions. To do so, they use mathematical tools like Linear Algebra to process, analyze, and visualize data. This course helps build a foundation in Linear Algebra, which is essential for Data Scientists to effectively perform their job duties. The course covers concepts like vectors, matrices, and linear transformations, which are all fundamental to data science.
Machine Learning Engineer
Machine Learning Engineers work at the intersection of computer science and mathematics to develop and implement machine learning models. Linear Algebra is a critical component of machine learning, as it provides the mathematical framework for understanding and manipulating data. This course provides a strong foundation in Linear Algebra, which is essential for Machine Learning Engineers to succeed in their roles. The course covers concepts like vectors, matrices, and linear transformations, which are all used extensively in machine learning.
Software Engineer
Software Engineers design, develop, and maintain software applications. Linear Algebra is becoming increasingly important in software engineering, as it provides a mathematical framework for understanding and manipulating data. This course provides a strong foundation in Linear Algebra, which is beneficial for Software Engineers working with data-intensive applications. The course covers concepts like vectors, matrices, and linear transformations, which are all used in software engineering.
Statistician
Statisticians collect, analyze, interpret, and present data. Linear Algebra is a fundamental tool for Statisticians, as it provides the mathematical framework for understanding and manipulating data. This course provides a strong foundation in Linear Algebra, which is essential for Statisticians to succeed in their roles. The course covers concepts like vectors, matrices, and linear transformations, which are all used extensively in statistics.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical methods to analyze financial data and make investment decisions. Linear Algebra is a core component of quantitative finance, as it provides the mathematical framework for understanding and manipulating data. This course provides a strong foundation in Linear Algebra, which is essential for Quantitative Analysts to succeed in their roles. The course covers concepts like vectors, matrices, and linear transformations, which are all used extensively in quantitative finance.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to solve complex business problems. Linear Algebra is a fundamental tool for Operations Research Analysts, as it provides the mathematical framework for understanding and manipulating data. This course provides a strong foundation in Linear Algebra, which is essential for Operations Research Analysts to succeed in their roles. The course covers concepts like vectors, matrices, and linear transformations, which are all used extensively in operations research.
Actuary
Actuaries use mathematical and statistical methods to assess risk and uncertainty. Linear Algebra is a fundamental tool for Actuaries, as it provides the mathematical framework for understanding and manipulating data. This course provides a strong foundation in Linear Algebra, which is essential for Actuaries to succeed in their roles. The course covers concepts like vectors, matrices, and linear transformations, which are all used extensively in actuarial science.
Financial Analyst
Financial Analysts use financial data to make investment recommendations. Linear Algebra is becoming increasingly important in financial analysis, as it provides the mathematical framework for understanding and manipulating data. This course provides a strong foundation in Linear Algebra, which is beneficial for Financial Analysts working with complex financial models. The course covers concepts like vectors, matrices, and linear transformations, which are all used in financial analysis.
Business Analyst
Business Analysts use data and analysis to solve business problems. Linear Algebra is a valuable tool for Business Analysts, as it provides the mathematical framework for understanding and manipulating data. This course provides a strong foundation in Linear Algebra, which is beneficial for Business Analysts working with complex data-driven projects. The course covers concepts like vectors, matrices, and linear transformations, which are all used in business analysis.
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. Linear Algebra is a valuable tool for Data Analysts, as it provides the mathematical framework for understanding and manipulating data. This course provides a strong foundation in Linear Algebra, which is beneficial for Data Analysts working with complex datasets. The course covers concepts like vectors, matrices, and linear transformations, which are all used in data analysis.
Risk Analyst
Risk Analysts use mathematical and statistical methods to assess risk and uncertainty. Linear Algebra is a fundamental tool for Risk Analysts, as it provides the mathematical framework for understanding and manipulating data. This course provides a strong foundation in Linear Algebra, which is essential for Risk Analysts to succeed in their roles. The course covers concepts like vectors, matrices, and linear transformations, which are all used extensively in risk analysis.
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior. Linear Algebra is a valuable tool for Market Researchers, as it provides the mathematical framework for understanding and manipulating data. This course provides a strong foundation in Linear Algebra, which is beneficial for Market Researchers working with complex datasets. The course covers concepts like vectors, matrices, and linear transformations, which are all used in market research.
Researcher
Researchers conduct original research in a variety of fields. Linear Algebra is a valuable tool for Researchers, as it provides a mathematical framework for understanding and analyzing data. This course provides a strong foundation in Linear Algebra, which is beneficial for Researchers working with complex datasets. The course covers concepts like vectors, matrices, and linear transformations, which are all used in research.
Teacher
Teachers educate and inspire students. Linear Algebra is a valuable tool for Teachers, as it provides a mathematical framework for understanding and presenting complex concepts. This course provides a strong foundation in Linear Algebra, which is beneficial for Teachers working with students in STEM fields. The course covers concepts like vectors, matrices, and linear transformations, which are all used in teaching mathematics and other STEM subjects.
Consultant
Consultants advise clients on a wide range of business issues. Linear Algebra is a valuable tool for Consultants, as it provides a mathematical framework for understanding and analyzing data. This course provides a strong foundation in Linear Algebra, which is beneficial for Consultants working with data-driven projects. The course covers concepts like vectors, matrices, and linear transformations, which are all used in consulting.

Reading list

We've selected 12 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 Linear Algebra Essentials.
More advanced treatment of linear algebra that is suitable for students who have already taken a basic course in the subject. It covers a wide range of topics, including matrix theory, linear equations, and eigenvalues.
Classic textbook on linear algebra that is widely used in undergraduate and graduate courses. It provides a comprehensive introduction to the subject, covering a wide range of topics from basic concepts to advanced applications.
More advanced treatment of linear algebra that is suitable for students who have already taken a basic course in the subject. It covers a wide range of topics, including matrix theory, numerical linear algebra, and applications.
More specialized treatment of linear algebra that is tailored to the needs of machine learning students. It covers a wide range of topics, including vectors, matrices, and linear transformations. It also includes a number of applications to machine learning.
Modern introduction to linear algebra that is accessible to students with a variety of backgrounds. It covers a wide range of topics, including vectors, matrices, and linear transformations. It also includes a number of applications to other fields, such as computer science and economics.
Widely used textbook for undergraduate linear algebra courses. It good choice for students who are looking for a comprehensive introduction to the subject.
Comprehensive introduction to linear algebra that is suitable for students with a variety of backgrounds. It covers a wide range of topics, including vectors, matrices, and linear transformations. It also includes a number of applications to other fields, such as physics, engineering, and computer science.
More concise and accessible introduction to linear algebra than Strang's book. It good choice for students who are looking for a less challenging introduction to the subject.
More applied introduction to linear algebra than most other textbooks. It good choice for students who are looking for a more practical understanding of the subject.
More concise and accessible introduction to linear algebra than Lay's book. It good choice for students who are looking for a less challenging introduction to the subject.
More specialized treatment of linear algebra that is tailored to the needs of economics students. It covers a wide range of topics, including vectors, matrices, and linear transformations. It also includes a number of applications to economics.

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