Topics to Build Numerical Capabilities

Knowing about data science subjects isn’t enough; a list of essential topics from each subject help beginners start their career in data science.

Mathematics

Mathematics is daunting for many people, but you don't need to learn everything at the start. There are mainly two topics in mathematics that you need to cover, and the important thing is having a clear understanding of each sub-topic that you study in each of these topics.

Linear algebra

In linear algebra, we study the properties of linear equations, vector spaces, and linear transformations, which include matrix algebra, eigenvalues, and eigenvectors. It helps solve the systems of linear equations, linear differential equations, and optimization problems.

The essential sub-topics of linear algebra are addition, subtraction, division, multiplication, square roots, exponents, summations, factorials, vector, scalar, matrix, matrix addition and multiplication, matrix scalar multiplication, identity matrices, trace, range, rank, inverse, transpose, nullspace, eigenvalues, the eigenvector of a matrix, determinants and their ...