Advanced Matrix Theory and Linear Algebra for Engineers
This course covers advanced matrix theory and linear algebra for engineers. It begins with a discussion of Singular Value Decomposition (SVD) Part 1, followed by a review of linear systems in Parts 1 and 2. The course concludes with an epilogue. Students will gain an understanding of SVD and linear systems, and how they can be applied to engineering problems. ▼
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Course Feature
Cost:
Free
Provider:
Youtube
Certificate:
Paid Certification
Language:
English
Start Date:
On-Demand
Course Overview
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Updated in [February 21st, 2023]
Singular Value Decomposition (SVD) Part 1 (CH_30).
Back To Linear Systems Part 2 (Ch-30).
Back To Linear Systems Part 1 (Ch-30).
Epilogue.
Back to Linear Systems Part 2.
Back to Linear Systems Part 1.
Singular value decomposition - Part 2.
Singular value decomposition - Part 1.
Hermitian and Symmetric Matrices Part 4.
Hermitian and Symmetric Matrices Part 3.
Hermitian and Symmetric matrices Part 1.
Diagonalization Part 4.
Diagonalization Part 3.
Diaggonalization Part 2.
Diagonalization Part 1.
Inner Product and Orthogonality Part 6.
Inner product and orthogonality Part 5.
Inner Product and Orthogonality Part 4.
Inner Product and Orthogonality Part 3.
Inner Product and Orthogonality Part 2.
Inner product and Orthogonality part 1.
Linear transformations - part 5.
Linear transformations - part 4.
Linear transformations - part 3.
Linear transformations - part 2.
Basis Part 3.
Linear Transformations - part 1.
Basis Part 1.
Linear independence and subspaces part 4.
Linear independence and subspaces part 3.
Linear Independence and subspaces part 2.
Linear Independence and subspaces part 1.
vector spaces part -2.
Linear transformations - part 5.
(Please note that we obtained the following content based on information that users may want to know, such as skills, applicable scenarios, future development, etc., combined with AI tools, and have been manually reviewed)
What skills and knowledge will you acquire during this course?
This course will provide students with the skills and knowledge to understand and apply advanced matrix theory and linear algebra for engineering applications. Specifically, students will learn about singular value decomposition (SVD), linear systems, hermitian and symmetric matrices, diagonalization, inner product and orthogonality, linear transformations, basis, linear independence and subspaces, and vector spaces. Additionally, students will gain an understanding of the mathematical principles and techniques used to solve engineering problems.
How does this course contribute to professional growth?
Advanced Matrix Theory and Linear Algebra for Engineers is a course that can contribute to professional growth by providing a comprehensive overview of linear algebra and matrix theory. The course covers topics such as singular value decomposition, hermitian and symmetric matrices, diagonalization, inner product and orthogonality, linear transformations, basis, linear independence and subspaces, and vector spaces. By understanding these topics, professionals can gain a better understanding of linear algebra and matrix theory, which can be applied to a variety of fields, such as engineering, mathematics, and computer science. This course can help professionals gain the knowledge and skills necessary to succeed in their respective fields.
Is this course suitable for preparing further education?
Advanced Matrix Theory and Linear Algebra for Engineers appears to be a suitable course for preparing for further education. The course covers a wide range of topics, including Singular Value Decomposition (SVD), Linear Systems, Hermitian and Symmetric Matrices, Diagonalization, Inner Product and Orthogonality, Linear Transformations, Basis, Linear Independence and Subspaces, and Vector Spaces. These topics are essential for understanding more advanced topics in mathematics and engineering.
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