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Basic Mathematics and Statistics for Non-Majors (Theory)

This course is a hands-on program for practicing the fundamentals of machine learning mathematics and statistics using Python. While machine learning and deep learning require programming skills, a mathematical background is essential to understand the underlying principles. Through this course, you can step-by-step master the foundational mathematics required for artificial intelligence!

(5.0) 2 reviews

50 learners

Level Beginner

Course period 12 months

Linear Algebra
Linear Algebra
Probability and Statistics
Probability and Statistics
Python
Python
Linear Algebra
Linear Algebra
Probability and Statistics
Probability and Statistics
Python
Python

What you will gain after the course

  • Differentiation using Python

  • Probability and Statistics using Python

  • Basic competencies in mathematics for artificial intelligence

Mathematics and Statistics Basics for Non-Majors <Theory Edition>


Basic Python syntax is used to conduct theory and practice on calculus, linear algebra, probability, and statistics.

While running toward a new career development, from data analysis to artificial intelligence,

Did you feel that a foundation in mathematics is necessary to grasp the principles?

Let's build a solid foundation from theory to practice, covering everything from calculus and linear algebra to probability and statistics.

(*This course is the theoretical version; the practical version requires a separate enrollment.)

What you will learn

Functions

  • Understanding basic function terminology

  • Comparison of mathematical functions and programming functions

  • Practice expressing functions for various types of data

  • Definition of the concept of linear functions


  • Identifying various non-linear functions

Calculus Theory

  • Concept and definition of derivatives

  • Understanding derivatives

  • Geometric meaning of differentiation

Linear Algebra Theory

  • Linear Algebra

    Understanding operations, inverse matrices, and the equation of a line

  • Understand the differences between scalars, vectors, and matrices

  • Understand square matrices, inverse matrices, identity matrices, and transposed matrices.

Basic Statistics

  • Identify the scope of what can be achieved through statistics-based data analysis

  • Representing data distribution

  • Understanding the concepts of trials requiring probability, sample spaces, and events

Distribution Inference Theory

  • Understanding the characteristics of normal distribution

  • Calculating probability values with data

Notes before taking the course

Prerequisite Knowledge and Important Notes

  • Since this course is divided into theory and practice, you must register for each course separately.

  • An understanding and foundation of basic Python functions are required.

Recommended for
these people

Who is this course right for?

  • Those who are non-majors and do not understand the principles of Python functions

  • Those who want to build a solid foundation in mathematics and statistics.

  • Someone who is just about to start programming

  • People who want to study the basic elements required for Python programming

Need to know before starting?

  • I need an understanding of basic Python syntax.

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