Complete linear algebra: theory and implementation in code
Machine learning, AI, data science, statistics, simulations, computer graphics, multivariate analysis, matrix decompositions, signal processing, and other computational sciences rely heavily on linear algebra.
Professionals use linear algebra in computers to solve real-world applications in machine learning, data science, statistics, and signal processing. The way linear algebra is presented in 30-year-old textbooks is different from how professionals use linear algebra in computers to solve real-world applications in machine learning, data science, statistics, and signal processing. The "determinant" of a matrix, for example, is crucial in linear algebra theory, but should you utilize it in practical applications? The solution may astound you, and it's right here in this course!
Complete linear algebra: theory and implementation in code is for you if you wish to understand the mathematical ideas of linear algebra and matrix analysis, as well as how to apply such concepts to data analytics on computers (e.g., statistics or signal processing). All of the math ideas will be implemented in MATLAB and Python.
Requirements:
- Basic understanding of high-school algebra (e.g., solve for x in 2x=5)
- Interest in learning about matrices and vectors!
- (optional) Computer with MATLAB, Octave, or Python (or Jupyter)
Who this course is for:
- Anyone interested in learning about matrices and vectors
- Students who want supplemental instruction/practice for a linear algebra course
- Engineers who want to refresh their knowledge of matrices and decompositions
- Biologists who want to learn more about the math behind computational biology
- Data scientists (linear algebra is everywhere in data science!)
- Statisticians
- Someone who wants to know the important math underlying machine learning
- Someone who studied theoretical linear algebra and who wants to implement concepts in computers
- Computational scientists (statistics, biological, engineering, neuroscience, psychology, physics, etc.)
- Someone who wants to learn about eigendecomposition, diagonalization, and singular value decomposition!
- Artificial intelligence students
Subtitles: English
Udemy Rating: 4.7/5.0
Enroll here: https://www.udemy.com/course/linear-algebra-theory-and-implementation/
