Algorithmic Linear Algebra and Analytical Geometry

Linear algebra and analytical geometry are the essential mathematical language for modern computing, underpinning fields from machine learning to computer graphics. This course provides a strong foundation in these critical areas, teaching you not just the mathematical rules, but how to approach solutions from an algorithmic perspective suitable for translation into code. What you'll learn: * Understand core concepts of vector spaces, linear independence, and geometric interpretations in 2D and 3D space. * Master matrix operations, including addition, multiplication, determinants, and inverses, essential for data manipulation. * Apply techniques for solving systems of linear equations using methods like Gaussian elimination and matrix decomposition. * Practice representing and performing geometric transformations (translation, rotation, scaling) using matrix algebra. * Learn how to conceptualize mathematical solutions as step-by-step algorithms, preparing you for efficient computational implementation. We begin by defining fundamental concepts and terminology, then move through vector algebra and matrix theory, culminating in practical methods for solving complex linear systems and applying transformations. This course is designed for absolute beginners in programming, IT, or data science who need a strong, practical mathematical foundation. No advanced prerequisites are required. Start building your essential mathematical toolkit for a career in technology today.