Linear Algebra Fundamentals
$249.00
Dive into the world of linear algebra with this comprehensive course covering vector spaces, matrices, linear transformations, eigenvalues, and eigenvectors. Essential for anyone pursuing careers in data science, machine learning, engineering, or physics.
What You'll Learn:
- Vector Spaces and Subspaces
- Matrix Operations and Properties
- Linear Transformations
- Eigenvalues and Eigenvectors
- Applications in Data Science
- Computational Techniques
Course Description
Linear Algebra Fundamentals provides a thorough introduction to one of the most important branches of mathematics. This course is designed for students and professionals who want to understand the mathematical foundations behind modern data science, machine learning, and engineering applications.
You'll learn through a combination of theoretical explanations and practical applications. Each concept is illustrated with real-world examples from computer graphics, data analysis, and engineering. The course includes interactive exercises, coding assignments, and projects that help solidify your understanding.
Perfect for computer science students, aspiring data scientists, engineers, and anyone interested in understanding the mathematics behind modern technology.
Course Curriculum
- Week 1: Vectors and Vector Spaces
- Week 2: Matrices and Matrix Operations
- Week 3: Linear Transformations
- Week 4: Determinants and Inverse Matrices
- Week 5: Eigenvalues and Eigenvectors
- Week 6: Applications and Final Project
Your Instructor
Prof. Michael Chen, Ph.D. Applied Mathematics
Professor Chen specializes in computational mathematics and has taught linear algebra to thousands of students at leading universities. His research focuses on applications of linear algebra in machine learning and data science.