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Mathematics

Basic Mathematics and Statistics for Non-Majors (Theory)

This course is a practical one that covers the fundamental concepts of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but also a mathematical background to grasp their principles. Through this course, you can steadily master the foundational math needed for AI!

(5.0) 2 reviews

50 learners

Level Beginner

Course period 12 months

  • SW School
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 & Statistics with Python

  • Basic mathematical competence for AI

Fundamentals of Mathematics and Statistics for Non-Majors <Theory>


We will use Python's basic grammar to cover the theory and practice of differentiation, linear algebra, probability, and statistics .

Running towards developing a new career, from data analysis to artificial intelligence

Have you ever felt like you needed a foundation in math to understand the principles?

From theory to practice, we will build a solid foundation in calculus, linear algebra, probability, and statistics.

(*This course is a theory course. Separate registration is required for the practical course.)

Learn about these things

function

  • Understanding basic function terminology

  • Comparing mathematical and programming functions

  • Practice functional expressions on various data

  • Definition of the concept of linear function


  • Understanding various nonlinear functions

Differential theory

  • Differentiation Concepts and Definitions

  • Understanding derivatives

  • Geometric meaning of differentiation

Linear algebra theory

  • linear algebra

    Understanding operations, inverse matrices, and equations of lines

  • Understand the difference between scalars, vectors, and matrices

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

Statistics Basics

  • Understanding the scope of what is possible through statistical data analysis

  • Data distribution representation

  • Understand the concepts of trials, sample spaces, and events that require probability.

Distributional inference theory

  • Understanding the characteristics of the normal distribution

  • Calculating probability values with data

Things to note before taking the course

Player Knowledge and Precautions

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

  • You need to have a basic understanding and knowledge of basic Python functions.

Recommended for
these people

Who is this course right for?

  • Non-majors for whom Python function principles are unclear

  • For those who want to build a foundation in Mathematics/Statistics

  • A person just starting programming

  • Person wanting to learn Python programming basics.

Need to know before starting?

  • I need to understand Python basic syntax.

Hello
This is

1,408

Learners

99

Reviews

5

Answers

4.7

Rating

15

Courses

Curriculum

All

9 lectures ∙ (2hr 54min)

Published: 
Last updated: 

Reviews

All

2 reviews

5.0

2 reviews

  • navruzbek19980884님의 프로필 이미지
    navruzbek19980884

    Reviews 7

    Average Rating 4.1

    5

    100% enrolled

    Difficult subject

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      jychoi0942

      Reviews 9

      Average Rating 5.0

      5

      100% enrolled

      $26.40

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