Introduction to Data Analysis

16 December 2022 - 31 December 2024 г.
The course has already started
226 days
Before the end of the enrollment
  • English

    course language

  • от 4 до 10 недель

    course duration

  • от 5 до 10 часов в неделю

    needed to educate

  • 2 credit points

    for credit at your university

  • Cost 3 600 Р

    for studying

Dear learners, please note that only part of the materials is available for free viewing. All course materials will be available after certification payment.

With this course, you will begin to take the first steps in the world of data analysis. You will see in detail the main concepts and processes that make up this discipline.



The main goal of the course is acquisition of knowledge about the mathematical and statistical basics underlying the main ideas and approaches used in data science. This is achieved through setting and solving typical tasks, which a researcher in the field of data science can face in his work. You will get practical skills in working with data analysis tools used in different spheres of human activity. You will be acquainted with the main tasks, methods and basic algorithms, as well as with the spheres of their practical applications. You will know how applied problems of data processing and analysis are being solved. You will be acquainted with the main concepts of artificial neural networks and the ways they are being trained.




The course does not require any special training

Course program

  1. Data and Big Data Analysis: Approaches, Functions and Software Tools
  2. Basic Characteristics of Data. Distributions, Statistics and Regressions.
  3. Clustering and Dimensionality Reduction
  4. Machine Learning and Artificial Neural Networks

Formed competencies

The course is aimed at the formation of general learning competencies for Bachelor’s and Specialists’ programs, as well as other competencies included in the education program.

ПК-2 Способность самостоятельно осуществлять постановку задачи статистического анализа и оценивания в избранной предметной области, выбор и применение статистического инструментария и программных средств.

ПК-3 Способность самостоятельно осваивать новые методы прикладной и математической статистики для их использования в аналитической работе.

ПК-4 Способность осознанно применять методы математической и дескриптивной статистики для анализа количественных данных, содержательно интерпретировать результаты

Education directions


Upon completion of this course, students will know:
1. methods of data analysis
2. basic characteristics of data


Upon completion of this course, students will get:
1. skills of analyze data using various tools


Upon completion of this course, students will be able to:
1. skills of working in specialized software

Отзывы о курсе

Руднев Владимир Александрович

Position: доцент кафедры вычислительной физики, доктор физико-математических наук


It is possible to get a certificate for this course.

The cost of passing the procedures for assessing learning outcomes with personal identification - 3600 Р.

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