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Mathematical Statistics Fundamentals (Theory) for Non-Majors

This course is a course that practices the basics of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but they also require a mathematical background to understand the principles. Through this course, you can gradually learn the basic mathematics required for artificial intelligence!

(5.0) 2 reviews

43 students

Linear Algebra
Probability and Statistics
Python

This course is prepared for Beginners.

What you will learn!

  • Differentiation using Python

  • Probability Statistics Using Python

  • Artificial intelligence is a basic ability in mathematics.

Basic 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 some mathematical foundation 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. A separate application is required for the practical course.)

Learn about these things

Function

  • Understanding basic function terminology

  • Comparison of mathematical and programming functions

  • Practice functional expressions on various data

  • Definition of the concept of linear function


  • Understanding various nonlinear functions

Differential theory

  • Differential 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

  • Understand what you can do with 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 normal distribution

  • Calculating probability values with data

Things to note before taking the class

Player Knowledge and Notes

  • 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 who do not understand the principles of Python functions

  • For those who want to build a foundation in mathematics/statistics

  • For people who are just starting out with programming

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

Need to know before starting?

  • I need to understand basic Python syntax.

Hello
This is medici

1,335

Students

88

Reviews

5

Answers

4.8

Rating

13

Courses

Curriculum

All

9 lectures ∙ (2hr 54min)

Published: 
Last updated: 

Reviews

All

2 reviews

5.0

2 reviews

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