Linear algebra is a useful skill for professionals in data science, machine learning, and AI. We just posted a course on the freeCodeCamp.org YouTube channel that will teach you linear algebra.
This crash course spans just over 6 hours and is a great starting point for beginners. It serves as the foundation for mastering linear algebra and sets you up for success in more advanced topics.
Tatev Aslanyan created this course. She is a seasoned Data Science and AI professional with over half a decade of international experience.
The course combines academic-level material with industry insights, leveraging resources and textbooks. You'll see how university concepts seamlessly translate into practical applications. The course features practical examples, including a detailed one-hour walkthrough of solving systems of linear equations with Gaussian elimination by hand, a core technique in linear algebra.
Course Structure
The course is divided into the following sections:
Introduction to the Course
Linear Algebra Roadmap for 2024
Course Prerequisites
Refreshment: Real Numbers and Vector Spaces
Refreshment: Norms and Euclidean Distance
Why These Prerequisites Matter
Foundations of Vectors
Vector - Geometric Representation Example
Special Vectors
Application of Vectors
Vector Operations and Properties
Advanced Vectors and Concepts
Length of a Vector - Definition and Example
Length of Vector - Geometric Intuition
Dot Product
Dot Product, Length of Vector, and Cosine Rule
Cauchy Schwarz Inequality - Derivation & Proof
Introduction to Linear Systems
Introduction to Matrices
Core Matrix Operations
Solving Linear Systems - Gaussian Elimination
Detailed Example - Solving Linear Systems
Detailed Example - Reduced Row Echelon Form (Augmented Matrix, REF, RREF)
Conclusion
This course offers a solid foundation in linear algebra, serving as a fantastic warm-up for anyone looking to explore generative AI in our upcoming courses. Watch the full course on the freeCodeCamp.org YouTube channel (6-hour watch).