Foundations of Linear Algebra
Master linear algebra: Learn vector spaces, matrices, and transformations with practical applications in data science and engineering problems.
Master linear algebra: Learn vector spaces, matrices, and transformations with practical applications in data science and engineering problems.
Dive into the essential concepts of linear algebra with this comprehensive course. Starting with systems of linear equations, you'll explore vectors, matrices, and linear transformations. The course emphasizes theoretical understanding alongside practical applications, covering key topics like basis and dimension, matrix operations, and inner products. You'll learn how these concepts apply to real-world problems in statistics, data science, economics, and engineering. Perfect for students seeking a solid foundation in linear algebra's language and theory.
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What you'll learn
Master the relationships between linear equations matrices and linear transformations
Understand vector and matrix operations including multiplication and inverses
Grasp the fundamental concepts of basis and dimension in vector spaces
Apply inner products and orthogonality to real-world problems
Develop proficiency in linear algebra vocabulary and theory
Utilize linear algebra concepts in statistics and data science applications
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, Exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This comprehensive course introduces the fundamental concepts of linear algebra, focusing on both theoretical understanding and practical applications. Students learn about systems of linear equations, vectors, matrices, and linear transformations, with emphasis on understanding the underlying principles. The course covers essential topics like matrix operations, basis and dimension, and inner products. Special attention is given to applications in statistics, data science, economics, and physics. The curriculum balances theoretical foundations with practical problem-solving skills.
Fee Structure
Instructor
Distinguished Mathematics Educator and Online Learning Pioneer
Stephen Wang serves as an Associate Teaching Professor of Mathematics at Rice University where he has been making significant contributions to mathematics education since 2015 His academic journey includes earning his PhD in Mathematics from the University of Chicago with a specialization in geometry His teaching excellence has been recognized with prestigious awards from both the University of Chicago and Harvard University demonstrating his exceptional ability to communicate complex mathematical concepts Prior to joining Rice he held faculty positions at Haverford College and Bucknell University where he continued to develop his innovative teaching methods His expertise extends beyond traditional classroom instruction as evidenced by his significant contribution to the development of the MIT Calculus course on edX demonstrating his commitment to making mathematics education accessible through digital platforms His teaching philosophy combines rigorous mathematical instruction with innovative pedagogical approaches making complex mathematical concepts accessible to students His work in online education particularly through the MIT Calculus course has helped shape how mathematics is taught in digital environments His expertise in geometry and mathematics education continues to influence both traditional and online learning environments making him a valuable asset in contemporary mathematics education His commitment to teaching excellence and innovation in mathematical education has made him a respected figure in both traditional and digital learning spaces.
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