We may earn an affiliate commission when you visit our partners.
Статистические методы анализа данных
Ульянкин Филипп Валерьевич
Ульянкин Филипп Валерьевич
В этом онлайн-курсе НИУ ВШЭ мы поговорим про статистические методы анализа данных. Мы подробно обсудим, как статистика связана с машинным обучением и какое место она занимает среди наук о данных. Поговорим о том, что есть два великих вопроса: "Как устроен...
Read more
В этом онлайн-курсе НИУ ВШЭ мы поговорим про статистические методы анализа данных. Мы подробно обсудим, как статистика связана с машинным обучением и какое место она занимает среди наук о данных. Поговорим о том, что есть два великих вопроса: "Как устроен...
Read more
В этом онлайн-курсе НИУ ВШЭ мы поговорим про статистические методы анализа данных. Мы подробно обсудим, как статистика связана с машинным обучением и какое место она занимает среди наук о данных. Поговорим о том, что есть два великих вопроса: "Как устроен мир?" и "Что будет дальше?". В зависимости от того, на какой вопрос мы ищем ответ, мы должны использовать разные методы.
Мы изучим метод максимального правдоподобия, поговорим про статистические свойства различных функций потерь. Поговорим о линейной регрессии и временных рядах. В конце курса мы обсудим байесовский подход к статистике и выясним, чем он отличается от частотного.
Register for this course and see more details by visiting:
OpenCourser.com/course/d6a7na/statisticheskie
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Guides learners how to approach data analysis, a ubiquitous skill used in myriad areas
Suitable for learners curious about machine learning and data science, fields that use statistics to explore data and extract insights
Explores both frequentist and Bayesian statistics, giving learners a robust understanding of these two main approaches
Save this course
Save Статистические методы анализа данных to your list so you can find it easily later:
Save
Save
Reviews summary
Highly rated statistics course
Based on three 5-star reviews, this online course on Statistical Methods of Data Analysis from HSE University receives high praise for its clear explanations of complex topics and engaging presentation. Students appreciate the instructor's ability to make challenging concepts accessible and find the course content valuable and informative.
Activities
Coming soon
We're preparing activities for
Статистические методы анализа данных.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Статистические методы анализа данных will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts use statistical methods to analyze data and extract insights. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in data analysis. Taking this course will help you develop the skills and knowledge you need to be a successful Data Analyst.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use statistical methods to develop and deploy machine learning models. This course provides a solid foundation in statistical methods, which is essential for success in machine learning. You will learn about maximum likelihood estimation, linear regression, and time series analysis, as well as the Bayesian approach to statistics. This knowledge will help you build and deploy machine learning models that are accurate and reliable.
Data Scientist
Data Scientist
Data Scientists use statistical methods to analyze data and solve business problems. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in data science. Taking this course will help you develop the skills and knowledge you need to be a successful Data Scientist.
Statistician
Statistician
Statisticians use statistical methods to analyze data and draw conclusions. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in statistics. Taking this course will help you develop the skills and knowledge you need to be a successful Statistician.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use statistical methods to analyze financial data and make investment decisions. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in quantitative finance. Taking this course will help you develop the skills and knowledge you need to be a successful Quantitative Analyst.
Actuary
Actuary
Actuaries use statistical methods to assess risk and make financial decisions. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in actuarial science. Taking this course will help you develop the skills and knowledge you need to be a successful Actuary.
Biostatistician
Biostatistician
Biostatisticians use statistical methods to analyze biological data. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in biostatistics. Taking this course will help you develop the skills and knowledge you need to be a successful Biostatistician.
Epidemiologist
Epidemiologist
Epidemiologists use statistical methods to study the distribution and determinants of health-related states or events in specified populations. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in epidemiology. Taking this course will help you develop the skills and knowledge you need to be a successful Epidemiologist.
Economist
Economist
Economists use statistical methods to analyze economic data and make policy recommendations. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in economics. Taking this course will help you develop the skills and knowledge you need to be a successful Economist.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use statistical methods to solve problems in business and industry. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in operations research. Taking this course will help you develop the skills and knowledge you need to be a successful Operations Research Analyst.
Market Researcher
Market Researcher
Market Researchers use statistical methods to collect and analyze data about consumers and markets. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in market research. Taking this course will help you develop the skills and knowledge you need to be a successful Market Researcher.
Research Analyst
Research Analyst
Research Analysts use statistical methods to analyze data and make recommendations. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in research. Taking this course will help you develop the skills and knowledge you need to be a successful Research Analyst.
Software Engineer
Software Engineer
Software Engineers use statistical methods to develop and test software. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in software engineering. Taking this course will help you develop the skills and knowledge you need to be a successful Software Engineer.
Data Architect
Data Architect
Data Architects use statistical methods to design and implement data management systems. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in data architecture. Taking this course will help you develop the skills and knowledge you need to be a successful Data Architect.
Business Analyst
Business Analyst
Business Analysts use statistical methods to analyze data and make recommendations. This course provides a comprehensive overview of statistical methods, including maximum likelihood estimation, linear regression, and time series analysis. It also covers the Bayesian approach to statistics, which is becoming increasingly popular in business analysis. Taking this course will help you develop the skills and knowledge you need to be a successful Business Analyst.
For more career information including salaries, visit:
OpenCourser.com/course/d6a7na/statisticheskie
Reading list
We've selected 13 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Статистические методы анализа данных.
This popular book covers a wide range of statistical topics, from basic concepts to advanced methods like supervised and unsupervised learning.
This introductory book on statistical learning, which is freely available online, is commonly used for academic courses and valuable reference in industry.
This classic book provides a comprehensive overview of statistical learning methods, including supervised and unsupervised learning. It valuable reference for practitioners and researchers in machine learning.
Provides a comprehensive and mathematical treatment of pattern recognition and machine learning. It valuable reference for researchers in machine learning and related fields.
Save
Provides a comprehensive and up-to-date overview of deep learning, including theoretical foundations and practical applications. It valuable reference for researchers and practitioners in deep learning.
Provides a comprehensive and up-to-date overview of probabilistic graphical models. It valuable reference for researchers and practitioners in machine learning and related fields.
Provides a comprehensive and accessible introduction to information theory, inference, and learning algorithms. It is suitable for beginners and those with some background in mathematics.
Provides a comprehensive and modern introduction to machine learning from a probabilistic perspective.
Provides a comprehensive and accessible introduction to reinforcement learning. It is suitable for beginners and those with some background in machine learning.
Provides a solid foundation in statistical methods, with a particular focus on applications to machine learning. While chapters are primarily theoretical, they are accessible to those without a background in statistics.
Provides a comprehensive and accessible introduction to Bayesian statistics, including theoretical foundations and practical applications.
Provides a practical introduction to Bayesian statistics using R and Stan. It is particularly useful for those with a background in statistics who want to learn Bayesian methods.
Provides a comprehensive and accessible introduction to convex optimization. It is suitable for beginners and those with some background in mathematics.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/d6a7na/statisticheskie
Share
Similar courses
Here are nine courses similar to
Статистические методы анализа данных.
Продвинутые методы машинного обучения
OpenCourser.com/course/ft4uoe/prodvinutye
Продвинутые методы машинного обучения
Most relevant
Сбор и анализ данных в Python
OpenCourser.com/course/n3n60c/sbor
Сбор и анализ данных в Python
Most relevant
Корпоративное право для не-юристов
OpenCourser.com/course/btq357/korporativnoe
Корпоративное право для не-юристов
Most relevant
Цифровая трансформация
OpenCourser.com/course/ncgaqx/tsifrovaia
Цифровая трансформация
Most relevant
Основы машинного обучения
OpenCourser.com/course/sid2yd/osnovy
Основы машинного обучения
Most relevant
Представление презентации
OpenCourser.com/course/9unt70/predstavlenie
Представление презентации
Most relevant
Статистика для обработки экспериментов и А/B-тестирования
OpenCourser.com/course/wz3pv6/statistika
Статистика для обработки экспериментов и А/B-тестирования
Most relevant
Математическая статистика и А/В тестирование
OpenCourser.com/course/rbzkkl/matematicheskaia
Математическая статистика и А/В тестирование
Most relevant
Обобщенные линейные модели
OpenCourser.com/course/0iczcs/obobshchennye
Обобщенные линейные модели
Most relevant
Time
24 hours
Via
Coursera
Institution
HSE University
Instructor
Ульянкин Филипп Валерьевич
Good to know
Guides learners how to approach data analysis, a ubiquitous skill used in myriad areas
Suitable for learners curious about machine learning and data science, fields that use statistics to explore data and extract insights
Explores both frequentist and Bayesian statistics, giving learners a robust understanding of these two main approaches
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser