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Lecture 1: The geometry of linear equations. Lecture 2: Elimination with matrices. Lecture 3: Multiplication and inverse matrices. Lecture 4: Factorization into A = LU. Lecture 5: Transposes, permutations, spaces R^n. Lecture 6: Column space and nullspace. Lecture 7: Solving Ax = 0: pivot variables, special solutions.
This syllabus section provides information on course goals, meeting times, prerequisites, required text, homework, exams, grading, and tools for numerical linear algebra.
This course covers matrix theory and linear algebra, emphasizing topics useful in other disciplines. Linear algebra is a branch of mathematics that studies systems of linear equations and the properties of matrices. The concepts of linear algebra are extremely useful in physics, economics and social sciences, natural sciences, and engineering.
18.06SC. Linear Algebra. View Course. Enroll to Get Started. About This Course. This course covers matrix theory and linear algebra, emphasizing topics useful in other disciplines. Linear algebra is a branch of mathematics that studies systems of linear equations and the properties of matrices.
Linear algebra is a branch of mathematics that studies systems of linear equations and the properties of matrices. The concepts of linear algebra are extremely useful in physics, economics and social sciences, natural sciences, and engineering.
Study Materials | Linear Algebra | Mathematics | MIT OpenCourseWare. Additional Materials from the Textbook. The textbook for this course is: Strang, Gilbert. Introduction to Linear Algebra. 4th ed. Wellesley-Cambridge Press, 2009. ISBN: 9780980232714. The Table of Contents, Preface, and selected chapters are freely available online.
Table of Contents for Introduction to Linear Algebra (5th edition 2016) 1 Introduction to Vectors. 1.1 Vectors and Linear Combinations. 1.2 Lengths and Dot Products. 1.3 Matrices. 2 Solving Linear Equations. 2.1 Vectors and Linear Equations. 2.2 The Idea of Elimination. 2.3 Elimination Using Matrices.
