Description:
The course is intended for those who want to start Data Science journey, but math knowledge does not allow you to feel confident enough; for those who want to refresh basic mathematics before delving into the data science; for those who do not want to make a reference to a math textbook every time when studying new algorithms.
Key skills:
In the course we will give a base that will allow you to easily learn new specialized sections of mathematics for Data Science. Recall the basic functions, their properties, operations with them; we will go through the basics of differentiation and integration and their application; we will get acquainted with sets and matrices, combinatorics and an introduction to probability theory.
Outline:
Schedule | Themes |
Equations and Inequalities; Quadratic Equations and Inequalities; Absolute Value | |
Exponentiation; Basic Rules for Exponentiation; Arithmetic, Geometric and Harmonic Progressions | |
Sets Definition; Basic Operations; Common Number Sets; Binary Relations | |
Introduction to Function; Domain of Definition; Range of the Function (Codomain); Even and Odd Functions; Periodic Function | |
Friday | Power Function; Inverse Function |
Logarithm; Exponential Function; Logarithmic Function | |
Trigonometry Basics; Trigonometric Functions | |
Vector; Line; Plane; Angle Between Geometry Objects | |
Introduction to Derivatives; Equation of a Tangent Line | |
Friday | Functions Monotony; Extrema of a Function; Concavity and Convexity of a Function |
Antiderivative: Rules, Formula & Examples. | |
The Indefinite Integral and Basic Rules of Integration. Area Under a Curve | |
Matrix of a Numbers, Basic Operations, Determinant | |
Basics of Combinatorics | |
Friday | Basic Concepts of Probability; Sum Rule; Product Rule; Unconditional Probability; Conditional Probability |