For many advanced courses in Machine Learning and Data Science, you will need to refresh yourself in math. This is because although you may have studied math in high school or university, it might not have been taught in an intuitive way that makes it easy to understand the concepts in Computer Science. This specialization bridges the gap by getting you up to speed in the underlying mathematics, and building an intuitive understanding. Linear algebra's first course focuses on linear algebra, and how it relates to data. Next we will examine vectors and matrixes, and how they can be used. The second course is Multivariate Calculus. This course builds on the previous one and focuses on optimizing fitting functions to ensure good data fits. It begins with an introduction to calculus and then uses the matrices and vectors from the previous course for data fitting. The third course is Dimensionality Reduction with Principal Component Analysis. This course uses the mathematics of the previous courses to reduce high-dimensional data. This course requires Python and numpy knowledge. This specialization will provide you with the mathematical knowledge required to continue your journey in machine-learning and enable you to take advanced courses.
