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Linear Algebra and Geometry 2

Much more about matrices; abstract vector spaces and their bases

Chapter 1: Abstract vector spaces and related stuff

S1. Introduction to the course

S2. Real vector spaces and their subspaces

You will learn: the definition of vector spaces and the way of reasoning around the axioms; determine whether a subset of a vector space is a subspace or not.S3. Linear combinations and linear independence

Read more

Linear Algebra and Geometry 2

Much more about matrices; abstract vector spaces and their bases

Chapter 1: Abstract vector spaces and related stuff

S1. Introduction to the course

S2. Real vector spaces and their subspaces

You will learn: the definition of vector spaces and the way of reasoning around the axioms; determine whether a subset of a vector space is a subspace or not.S3. Linear combinations and linear independence

You will learn: the concept of linear combination and span, linearly dependent and independent sets; apply Gaussian elimination for determining whether a set is linearly independent; geometrical interpretation of linear dependence and linear independence.

S4. Coordinates, basis, and dimension

You will learn: about the concept of basis for a vector space, the coordinates w.r.t.\ a given basis, and the dimension of a vector space; you will learn how to apply the determinant test for determining whether a set of n vectors is a basis of R^n.

S5. Change of basis

You will learn: how to recalculate coordinates between bases by solving systems of linear equations, by using transition matrices, and by using Gaussian elimination; the geometry behind different coordinate systems.

S6. Row space, column space, and nullspace of a matrix

You will learn: concepts of row and column space, and the nullspace for a matrix; find bases for span of several vectors in R^n with different conditions for the basis.

S7. Rank, nullity, and four fundamental matrix spaces

You will learn: determine the rank and the nullity for a matrix; find orthogonal complement to a given subspace; four fundamental matrix spaces and the relationship between them.

Chapter 2: Linear transformations

S8. Matrix transformations from R^n to R^m

You will learn: about matrix transformations: understand the way of identifying linear transformations with matrices (produce the standard matrix for a given transformation, and produce the transformation for a given matrix); concepts: kernel, image and inverse operators; understand the link between them and nullspace, column space and inverse matrix.

S9. Geometry of matrix transformations on R^2 and R^3

You will learn: about transformations such as rotations, symmetries, projections and their matrices; you will learn how to illustrate the actions of linear transformations in the plane.

S10. Properties of matrix transformations

You will learn: what happens with subspaces and affine spaces (points, lines and planes) under linear transformations; what happens with the area and volume; composition of linear transformations as matrix multiplication.

S11. General linear transformations in different bases

You will learn: solving problems involving linear transformations between two vector spaces; work with linear transformations in different bases.

Chapter 3: Orthogonality

S12. Gram-Schmidt Process

You will learn: about orthonormal bases and their superiority above the other bases; about orthogonal projections on subspaces to R^n; produce orthonormal bases for given subspaces of R^n with help of Gram-Schmidt process.

S13. Orthogonal matrices

You will learn: definition and properties of orthonormal matrices; their geometrical interpretation.

Chapter 4: Intro to eigendecomposition of matrices

S14. Eigenvalues and eigenvectors

You will learn: compute eigenvalues and eigenvectors for square matrices with real entries; geometric interpretation of eigenvectors and eigenspaces.

S15. Diagonalization

You will learn: to determine whether a given matrix is diagonalizable or not; diagonalize matrices and apply the diagonalization for problem solving (the powers of matrices).

S16. Wrap-up Linear Algebra and Geometry 2

You will learn: about the content of the third course.

S17. Extras

You will learn: about all the courses we offer. You will also get a glimpse into our plans for future courses, with approximate (very hypothetical. ) release dates.

Make sure that you check with your professor what parts of the course you will need for your final exam. Such things vary from country to country, from university to university, and they can even vary from year to year at the same university.

A detailed description of the content of the course, with all the 214 videos and their titles, and with the texts of all the 153 problems solved during this course, is presented in the resource file

"001 List_of_all_Videos_and_Problems_Linear_Algebra_and_Geometry_2.pdf”

under video 1 ("Introduction to the course"). This content is also presented in video 1.

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Builds a strong foundation for understanding advanced matrix concepts, making it suitable for students pursuing higher-level mathematics or computer science
Taught by Dr. Howard Anton, a renowned professor of mathematics with a wealth of experience and expertise in linear algebra
Explores topics such as vector spaces, matrices, transformations, and orthogonality, which are essential for various fields, including computer graphics, engineering, and physics
Suitable for students from various backgrounds, including high school students preparing for higher mathematics coursework, and college students majoring in STEM or business
Covers a comprehensive range of topics in linear algebra and geometry, making it a comprehensive resource for students seeking a solid understanding of the subject
Requires students to have a strong understanding of basic algebra and trigonometry, which may be a potential barrier for some learners

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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 and Geometry 2 with these activities:
Linear Algebra Concepts Review
Review foundational concepts in linear algebra to strengthen understanding before starting the course.
Browse courses on Vector Spaces
Show steps
  • Summarize key concepts from previous linear algebra coursework
  • Review notes and textbooks to refresh memory
  • Solve practice problems to test understanding
Linear Algebra Notes Digest
Compile comprehensive notes that summarize key concepts and theorems from the course.
Browse courses on Linear Algebra
Show steps
  • Review course materials and identify key concepts
  • Organize and summarize information in a structured format
  • Include examples and illustrations to aid understanding
  • Proofread and revise notes for clarity and accuracy
Introduction to Linear Algebra by Gilbert Strang
Review a comprehensive textbook to strengthen foundational understanding of linear algebra concepts.
Show steps
  • Read and summarize key chapters
  • Work through practice problems
  • Reflect on how concepts relate to the course
Five other activities
Expand to see all activities and additional details
Show all eight activities
Matrix Operations Challenge
Solve various matrix operation problems to solidify understanding of matrix operations.
Browse courses on Linear Algebra
Show steps
  • Review matrix operations concepts
  • Practice solving matrix operation problems
  • Solve increasingly complex matrix operation problems
Vector Space Problem Solving
Engage in targeted practice to improve problem-solving skills related to vector spaces.
Browse courses on Vector Spaces
Show steps
  • Review vector space concepts
  • Solve practice problems involving linear combinations, dependence, and independence
  • Analyze solutions and identify patterns
Study Group for Linear Transformations
Join a study group to collaborate on understanding linear transformations and related concepts.
Browse courses on Linear Transformations
Show steps
  • Find a group of peers with complementary skills
  • Set regular meeting times and establish a study plan
  • Work together to solve problems and clarify doubts
Eigenvalue and Eigenvector Tutorial
Follow online tutorials to deepen understanding of eigenvalues, eigenvectors, and their applications.
Show steps
  • Identify reputable online resources
  • Watch video tutorials and read accompanying materials
  • Complete practice exercises and review concepts
Presentation on Orthogonal Matrices
Create a presentation to showcase understanding of orthogonal matrices and their properties.
Browse courses on Orthogonal Matrices
Show steps
  • Research orthogonal matrices and their applications
  • Develop a presentation outline
  • Create slides and prepare visual aids
  • Practice delivering the presentation

Career center

Learners who complete Linear Algebra and Geometry 2 will develop knowledge and skills that may be useful to these careers:
Data Scientist
A Data Scientist builds models for analysis of data. These models may be for prediction, classification, or more. As a Data Scientist, it is typical to use linear algebra in the creation of these models. Linear Algebra and Geometry 2 may be useful for a Data Scientist as it covers topics which include matrices, abstract vector spaces, linear combinations, basis, and more.
Financial Analyst
A Financial Analyst uses math and computer programs to analyze data and help make business decisions. Linear algebra is used to make predictions and build models. Linear Algebra and Geometry 2 covers topics that may be helpful for this role such as matrices, abstract vector spaces, linear combinations, and more.
Operations Research Analyst
Operations Research Analysts use advanced analytical methods to improve business processes and maximize efficiency. Linear Algebra and Geometry 2 may be helpful for this role as it covers a number of topics which include matrices, abstract vector spaces, linear combinations, basis, and more.
Quantitative Analyst
Quantitative Analyst use mathematical and statistical modeling to identify investment opportunities. Linear Algebra and Geometry 2 may be helpful for this role because it covers topics which include matrices, abstract vector spaces, linear combinations, basis, and more.
Statistician
A Statistician collects, analyzes, interprets, and presents data. They use statistical methods to help solve problems in a variety of fields. Linear Algebra and Geometry 2 may be useful for this role as it covers topics such as matrices, abstract vector spaces, linear combinations, basis, and more.
Software Engineer
Software Engineers design, develop, and maintain software systems. Linear algebra is often used in the development of software for graphics and simulations. Linear Algebra and Geometry 2 may be useful for this role as it covers topics like matrices, abstract vector spaces, linear combinations, and more.
Actuary
An Actuary analyzes the financial consequences of risk. They use mathematical and statistical models to help businesses and individuals plan for the future. Linear Algebra and Geometry 2 may be useful for this role as it covers a number of topics such as matrices, abstract vector spaces, linear combinations, basis, and more.
Data Analyst
A Data Analyst collects, analyzes, and interprets data. They use data to help businesses make better decisions. Linear Algebra and Geometry 2 may be useful for this role as it covers a number of topics such as matrices, abstract vector spaces, linear combinations, and more.
Economist
An Economist analyzes economic data to help businesses and governments make decisions. Linear Algebra and Geometry 2 may be useful for this role as it covers a number of topics which include matrices, abstract vector spaces, linear combinations, basis, and more.
Market Researcher
A Market Researcher conducts research to help businesses better understand their customers. Linear Algebra and Geometry 2 may be useful for this role as it covers a number of topics which include matrices, abstract vector spaces, linear combinations, and more.
Operations Manager
An Operations Manager plans and oversees the operations of an organization. Linear Algebra and Geometry 2 may be useful for this role as it covers topics which include matrices, abstract vector spaces, linear combinations, basis, and more.
Product Manager
A Product Manager is responsible for the planning, development, and marketing of a product. Linear Algebra and Geometry 2 may be useful for this role as it covers a number of topics such as matrices, abstract vector spaces, linear combinations, and more.
Risk Manager
A Risk Manager analyzes and manages risks for an organization. Linear Algebra and Geometry 2 may be useful for this role as it covers a number of topics which include matrices, abstract vector spaces, linear combinations, basis, and more.
Teacher
A Teacher develops and delivers educational instruction to students. Linear Algebra and Geometry 2 may be useful for this role as it covers a number of topics which include matrices, abstract vector spaces, linear combinations, basis, and more.
Technical Writer
A Technical Writer creates and maintains technical documentation. Linear Algebra and Geometry 2 may be useful for this role as it covers a number of topics which include matrices, abstract vector spaces, linear combinations, basis, and more.

Reading list

We've selected 13 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 and Geometry 2.
This classic textbook provides a comprehensive treatment of linear algebra, including theoretical foundations and a wide range of applications. It is suitable for advanced undergraduate and graduate students.
This classic textbook provides a comprehensive introduction to linear algebra, covering a wide range of topics relevant to the course. It includes numerous solved examples and exercises to reinforce the concepts.
This advanced textbook provides a comprehensive treatment of linear algebra, including topics such as tensor analysis, spectral theory, and harmonic analysis. It is suitable for graduate students and researchers in mathematics.
This textbook offers a modern and accessible approach to linear algebra, emphasizing the connections between theory and applications. It includes a wealth of worked-out examples and problem sets.
This popular study guide provides a concise summary of linear algebra concepts, along with hundreds of solved problems. It is particularly useful for students who need extra practice or reinforcement.
This classic textbook provides a concise and elegant introduction to linear algebra and geometry. It is suitable for advanced undergraduate and graduate students with a strong mathematical background.
This comprehensive textbook provides a rigorous treatment of linear algebra, including advanced topics such as vector spaces, matrices, and determinants. It is suitable for more advanced students or as a reference for professionals.
This introductory textbook provides a balance of theory and applications of linear algebra, making it suitable for students in a variety of fields. It includes numerous examples and exercises to reinforce the concepts.
Provides an in-depth treatment of matrix theory, focusing on advanced topics such as singular value decomposition, canonical forms, and matrix functions. It is suitable for graduate students and researchers in mathematics.
This introductory textbook provides a concise and clear introduction to vector spaces and matrices, emphasizing the geometric and algebraic aspects. It is suitable for students with a basic understanding of mathematics.
This introductory textbook provides a clear and intuitive introduction to linear algebra, suitable for beginners with minimal mathematical background. It is particularly useful for students who need a basic understanding of the subject for further studies.

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