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Linear Algebra – Fundamentals & Applications

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About Course

This course provides a comprehensive introduction to Linear Algebra, covering essential concepts such as matrices, vector spaces, determinants, eigenvalues, and transformations. It is designed for students, engineers, computer scientists, and anyone interested in mastering the mathematical foundation of modern applications like AI, physics, and economics.

What Will You Learn?

  • ✅ Understand the Fundamentals of Linear Algebra – Learn the core concepts, including vectors, matrices, and transformations.
  • ✅ Perform Matrix Operations – Master addition, multiplication, transposition, and inversion of matrices.
  • ✅ Solve Systems of Linear Equations – Use Gaussian elimination, Cramer’s Rule, and matrix methods to find solutions.
  • ✅ Compute Determinants & Their Applications – Learn how determinants are used in solving equations and transformations.
  • ✅ Find Eigenvalues & Eigenvectors – Understand their significance in physics, AI, and engineering applications.
  • ✅ Work with Vector Spaces & Transformations – Explore basis, dimension, kernel, range, and linear mappings.
  • ✅ Apply Orthogonality & Inner Products – Use dot products, projections, and Gram-Schmidt orthogonalization.
  • ✅ Use Linear Algebra in Real-World Applications – AI, machine learning, physics, economics, and computer graphics.

Course Content

Introduction to Linear Algebra

  • Understanding the importance of Linear Algebra
  • Real-world applications in science, engineering, and AI
  • Basic mathematical notation and concepts

Vectors and Vector Spaces

Matrices and Matrix Operations

Determinants and Their Properties

Systems of Linear Equations

Eigenvalues and Eigenvectors

Linear Transformations

Inner Product Spaces and Orthogonality

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3 years ago
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