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Linear Algebra: Orthogonality and Diagonalization
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Linear Algebra: Orthogonality and Diagonalization

This course is part of Linear Algebra from Elementary to Advanced.

Course Cost

Free course

Intermediate

Skill Level

8 Hours

Self-paced lessons

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Linear Algebra from Elementary to Advanced Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

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4.9

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English

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What you'll learn

  • Master orthogonal vector operations and dot products

  • Understand orthogonal projections and transformations

  • Apply the Gram-Schmidt process

  • Analyze symmetric matrices and their properties

  • Solve least-squares problems

Skills you'll gain

Linear Algebra
Matrix Theory
Orthogonality
Diagonalization
Vector Spaces
Gram-Schmidt Process
Symmetric Matrices
Quadratic Forms
Eigenvalues
Machine Learning Applications

This course includes:

2.6 Hours PreRecorded video

11 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

Get a Completion Certificate

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Certificate
Certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

CREATED BY

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PROVIDED BY

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Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

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There are 4 modules in this course

This comprehensive course focuses on advanced linear algebra concepts, particularly orthogonality and diagonalization. Students learn about orthogonal vectors, transformations, and symmetric matrices, with applications to AI and machine learning. The curriculum covers dot products, orthogonal projections, the Gram-Schmidt process, and quadratic forms. Special emphasis is placed on symmetric matrices and their eigenspaces, which are crucial for data science applications.

Orthogonality

Module 1 · 2 Hours to complete

Orthogonal Projections and Least Squares Problems

Module 2 · 3 Hours to complete

Symmetric Matrices and Quadratic Forms

Module 3 · 2 Hours to complete

Final Assessment

Module 4 · 0 Hours to complete

Fee Structure

Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Linear Algebra from Elementary to Advanced

Reviews

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Linear Algebra: Orthogonality and Diagonalization

Intermediate

Skill Level

8 Hours

Self-paced lessons

Course Cost

Free course

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.