Eigenvalues Courses and Certifications

NPTEL;  IISc Bangalore

Advanced Matrix Theory and Linear Algebra for Engineers

1 rating

Comprehensive exploration of advanced linear algebra concepts for engineers, covering vector spaces, transformations, orthogonality, diagonalization, and singular value decomposition.

• YouTube
• 1 day 14 hours
• Self-Paced
• Free Video

Steve Brunton

Linear Systems - Control Bootcamp

1 rating

Analyze ordinary differential equations using eigenvalues and eigenvectors, laying the foundation for linear control theory in this comprehensive mathematical exploration.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

NPTEL;  IIT Bombay

Basic Linear Algebra

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

• YouTube
• 16 hours
• Self-Paced
• Free Video

NPTEL;  IIT Madras

Dynamics of Ocean Structures

Explore ocean structure dynamics, from types and environmental forces to vibration analysis and stochastic dynamics. Learn about platforms, fluid-structure interaction, and response control methods.

• YouTube
• 1 day 17 hours
• Self-Paced
• Free Video

Khan Academy

Null Space and Column Space Basis - Vectors and Spaces - Linear Algebra - Khan Academy

Learn to determine null space and column space basis for matrices, essential concepts in linear algebra for understanding vector spaces and transformations.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

Khan Academy

Parametric Representations of Lines - Vectors and Spaces - Linear Algebra - Khan Academy

Explore parametric representations of lines in R2 and R3, a fundamental concept in linear algebra. Learn to visualize and understand multi-dimensional mathematical reasoning.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

Khan Academy

Vector Examples - Vectors and Spaces - Linear Algebra - Khan Academy

Explore visual understanding of basic vector operations in linear algebra. Learn to visualize and manipulate vectors in multiple dimensions, enhancing your grasp of mathematical concepts.

• YouTube
• 26 minutes
• Self-Paced
• 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
• Self-Paced
• Free Video

Richard Behiel

The Hydrogen Atom: Introduction to Quantum Physics - Part 1

Dive into quantum physics fundamentals through an exploration of the hydrogen atom, covering electron behavior, Schrödinger's equation, and essential mathematical concepts in spherical coordinates.

• YouTube
• 19 minutes
• Self-Paced
• Free Video

Insights into Mathematics

Geometric Linear Algebra

Discover a visual approach to linear algebra emphasizing geometry, logic, and exact arithmetic through vectors, matrices, transformations, and applications to physics and geometry.

• YouTube
• 1 day 9 hours 34 minutes
• Self-Paced
• Free Video

Tom Rocks Maths

Oxford Linear Algebra

Master university-level linear algebra through Oxford's first-year curriculum covering matrices, determinants, eigenvalues, vector spaces, transformations, and inner products.

• YouTube
• 8 hours 6 minutes
• Self-Paced
• Free Video

For the Love of Physics

Advanced Quantum Mechanics

Dive into advanced quantum mechanics concepts including Dirac notation, Hilbert spaces, operators, uncertainty principles, and the mathematical foundations of QM theory.

• YouTube
• 5 hours 26 minutes
• Self-Paced
• Free Video

Instituto de Matemática Pura e Aplicada

Systolic and Diastolic Geometry - Eigenvalues and Minimal Surfaces

Delve into the relationship between eigenvalues and minimal surfaces in systolic and diastolic geometry with Mikhail Karpukhin's mathematical exploration of geometric comparison problems.

• YouTube
• 51 minutes
• Self-Paced
• Free Video

Face Recognition Techniques and Applications - Lecture 14

Explore face recognition techniques, from simple approaches to advanced methods like PCA and Linear Discriminant Analysis. Learn about eigenvectors, image compression, and scatter matrices.

• YouTube
• 1 hour 11 minutes
• Self-Paced
• Free Video

University of Tübingen

Mathematics for Machine Learning

Comprehensive exploration of linear algebra, calculus, probability theory, and statistics essential for machine learning, covering fundamental concepts to advanced applications.

• YouTube
• 1 day 17 hours
• Self-Paced
• Free Online Course