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Mathematics

Mathematical Statistics Basics for Non-Majors (Practical)

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.

18 learners are taking this course

  • SW School
함수
미분
3시간 만에 완강할 수 있는 강의 ⏰
Linear Algebra
Probability and Statistics
Python
Machine Learning(ML)
Deep Learning(DL)

What you will learn!

  • Taxi fare prediction using pseudoinverse matrix

  • Data representation using functions

  • Understand the concepts of probability, required trials, sample space, and events.

  • Calculate probability values from data and infer posterior probabilities for specific events.

Fundamentals of Mathematics and Statistics for Non-Majors <Practical Edition>


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

Have you been pursuing a new career in fields like data analysis and artificial intelligence, but felt the need for a solid foundation in mathematics to understand the principles? Build a solid foundation from theory to practice, covering everything from differentiation, linear algebra, probability, and statistics.


*This course is a practical course, so please complete the theory section before taking it.

Learn about these things


function

  • Understand 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?

  • 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 recommend this to those who have completed the basics of mathematical statistics (theory) for non-majors.

  • I need to understand basic Python syntax.

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1,353

Learners

93

Reviews

5

Answers

4.8

Rating

13

Courses

Curriculum

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5 lectures ∙ (2hr 6min)

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