Eigenvalues Courses and Certifications

IIT Roorkee;  NPTEL

Matrix Analysis with Applications

Comprehensive exploration of matrix theory and applications, covering computations, transformations, iterative methods, and specialized topics for engineering and science students.

• Swayam
• 8 weeks
• On-Demand
• Free Online Course

Linear Algebra Through Geometry

Holistic approach to linear algebra, blending algebraic and geometric perspectives. Emphasizes intuition and visualization to enhance understanding of vector spaces, subspaces, eigenvectors, and linear equations.

• Swayam
• 12 weeks
• On-Demand
• Free Online Course

IIT Roorkee;  NPTEL

Numerical Methods

Learn essential numerical methods for engineering problems, including linear equations, interpolation, and differential equations. Gain practical skills applicable across various technical fields.

• Swayam
• 12 weeks
• On-Demand
• Free Online Course

Beijing Jiaotong University

Linear Algebra with Applications

Master fundamental linear algebra concepts and their real-world applications, from solving linear equations to web search algorithms, population modeling, and computer image transformation.

• XuetangX
• On-Demand
• Free Online Course

IIT Bombay;  NPTEL

Basic Linear Algebra

Linear Algebr is a basic course for students intended to go for Engineering sudies and higher studies in Mathematics. We will cover the basic tools needed in these brances.

• Swayam
• 8 weeks
• On-Demand
• Free Online Course

IISc Bangalore;  NPTEL

Linear Algebra

Comprehensive introduction to linear algebra, covering vectors, matrices, transformations, and advanced concepts. Suitable for undergraduates in mathematics, physics, engineering, and computer science.

• Swayam
• 12 weeks
• On-Demand
• Free Online Course

IIT Madras;  NPTEL

Applied Linear Algebra

Explore advanced linear algebra concepts and their applications in engineering, including vector spaces, linear transformations, eigenvalues, and matrix decompositions.

• Swayam
• 12 weeks
• On-Demand
• Free Online Course

Introduction to Linear Algebra

Get familiar with matrices, vectors, and more as you explore the theory and real-world applications of linear algebra.

• Brilliant
• 30-40 hours
• On-Demand
• Paid Course

Linear Algebra - Vol 2

Explore advanced linear algebra concepts including transformation matrices, determinants, cofactors, eigenvalues, and eigenvectors through comprehensive lessons and practical examples.

• YouTube
• 1 hour 30 minutes
• On-Demand
• Free Video

Serrano.Academy

Principal Component Analysis

Explore dimensionality reduction through PCA, covering variance, covariance, eigenvectors, and eigenvalues. Learn key concepts with visual explanations and practical applications in data analysis.

• YouTube
• 27 minutes
• On-Demand
• Free Video

statisticsmatt

Matrices

Explore advanced matrix concepts including Kronecker product, spectral decomposition, singular value decomposition, and projection matrices, with applications in statistics and linear algebra.

• YouTube
• 4 hours 30 minutes
• On-Demand
• Free Video

Advanced Engineering Mathematics

Comprehensive exploration of advanced mathematical concepts, including complex analysis, transforms, probability, linear algebra, and more, with applications to engineering problems.

• YouTube
• 1 day 10 hours
• On-Demand
• Free Video

Professor Dave Explains

Linear Algebra

Comprehensive exploration of linear algebra concepts, from matrices and vector spaces to eigenvalues and transformations, with practical applications and in-depth explanations.

• YouTube
• 3 hours 30 minutes
• On-Demand
• Free Video

Steve Brunton

Topics in Dynamical Systems - Fixed Points, Linearization, Invariant Manifolds, Bifurcations & Chaos

Explore dynamical systems: fixed points, linearization, manifolds, bifurcations, and chaos. Gain insights into nonlinear dynamics and their applications in describing our changing world.

• YouTube
• 32 minutes
• On-Demand
• Free Video

Steve Brunton

Solving Systems of Differential Equations with Eigenvalues and Eigenvectors

Learn to solve systems of linear ODEs using eigenvalues and eigenvectors. Covers problem setup, solution methods, and intuitive interpretation, with code examples in Python and MATLAB.

• YouTube
• 22 minutes
• On-Demand
• Free Video