Staff member

### What you’ll learn​

• Gain Deep Understanding Of Linear Algebra Theoretically, Conceptually & Practically.
• Obtain A Very Robust Mathematical Foundation For Machine & Deep Learning, Computer Graphics, And Control Systems.
• Learn How To Use Both Python And Matlab For Solving & Visualizing Linear Algebra Problems.
• [Matrix Calculus] Learn How To Differentiate & Optimize Complex Equations Involving Matrices.
• Learn A Lot About Data Science, Co-variance Matrices, And The PCA.
• Learn About Linear Regression, The Normal Equation, And The Projection Matrix.
• Learn About Singular Value Decompositions Formally & Conceptually.
• Learn About Inverses And Pseudo Inverses.
• Learn About Determinants And Positive Definite Matrices.
• Learn How To Solve Systems Of Linear, Difference, & Differential Equations Both By Hand And Software.
• Learn About Lagrange Multipliers & Taylor Expansion.
• Learn About The Hessian Matrix And Its Importance In Multi-variable Calculus & Optimizations.
• Learn About Complex Transformation Matrices Like The Matrix To Perform Rotation Around An Arbitrary Axis In 3D.

### Requirements​

• Be familiar with Linear Algebra basics such as Vectors, Matrices, Dot Products, Cross Products, and Systems Of Linear Equations.
• For some of the advanced topics presented, I might require you to know some specific topics like partial differentiation or Laplace transform. However, you can easily skip those topics and still completely understand the subsequent sections.

### Who this course is for:​

• Anyone Interested In Linear Algebra, especially, but not limited to, in the context of computer engineering, computer science, or data-science.
• Anyone Interested In Machine Learning & Deep learning.
• Anyone Interested In Computer Graphics & Game Development.
• Anyone Interested In Classical Control Systems & Robotics.
• Anyone Interested To know how to use python & matlab for Linear Algebra.
• Anyone Interested In Linear Algebra Theories, Concepts, And Proofs.

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