from 4 to 10 weeks
from 5 to 10 hours per week
2 credit units
English languageThe certificate is issued on condition of successful completion of control tasks and passing the final certification test with proctoring.
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.
Online
The course does not require any special training
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
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
The course has already started
СПбГУThe course has already startedThe course has already started
Position: доцент кафедры вычислительной физики, доктор физико-математических наук
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Санкт-Петербургский государственный университет