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Сбор и анализ данных в Python

Ульянкин Филипп Валерьевич
В этом онлайн-курсе НИУ ВШЭ мы познакомимся с базовыми понятиями статистики, научимся аккуратно собирать данные, обрабатывать их и визуализировать. Также мы поговорим про базовые теоремы, которые используются в математической статистике: ЗБЧ и ЦПТ. В онлайн...
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В этом онлайн-курсе НИУ ВШЭ мы познакомимся с базовыми понятиями статистики, научимся аккуратно собирать данные, обрабатывать их и визуализировать. Также мы поговорим про базовые теоремы, которые используются в математической статистике: ЗБЧ и ЦПТ. В онлайн-курсе мы изучим основы математической статистики и аккуратную работу с данными. Мы научимся собирать и обрабатывать данные с помощью Python, поговорим про их визуализацию и предварительный анализ. Мы также познакомимся с основными распределениями и описательными статистиками, с которыми аналитики сталкиваются на повседневной основе. И обсудим теоремы, на которых базируется вся наука о данных: закон больших чисел и центральную предельную теорему. Github со всеми материалами курса: https://github.com/FUlyankin/matstat_online Курс состоит из 5 недель. Каждая включает в себя несколько коротких видеолекций (суммарная продолжительность – от 60 до 100 минут), тест на знание теоретического материала (5 – 15 вопросов), а также тест, включающий в себя выполнение заданий по программированию и решение теоретических задач. На некоторых неделях задание по программированию заменено заданием на взаимное оценивание. В конце курса предусмотрен итоговый экзамен, состоящий из тестовых вопросов.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Builds a strong foundation for beginners who are new to data analysis
Develops core skills in data collection, processing, visualization, and statistical analysis, which are essential for data analysts
Taught by recognized instructors from National Research University Higher School of Economics, who are experts in statistics and data analysis
Provides a comprehensive overview of mathematical statistics, including basic concepts, theorems, and distributions
Offers hands-on labs and interactive exercises to reinforce learning and develop practical skills
Includes a mix of video lectures, readings, and assignments to cater to diverse learning styles

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Reviews summary

Comprehensive data analysis in python

This course will teach you data collection, processing, and visualization in Python. You will also delve into theorems in mathematical statistics. Reviews praise the course for its clear explanations, engaging instructor, and practical programming assignments.
Provides helpful resources
"А за репозиторий на Github огромная благодарность!!!!"
Covers useful analysis methods
"Понравилось, что помимо основных тем мимоходом раскрываются полезные методы анализа данных(RFM, когортный анализ)"
Useful programming tasks
"Понравилось, что помимо основных тем мимоходом раскрываются полезные методы анализа данных..."
"Очень полезный курс. В особенности, нравится, что объясняется как та или иная теорема, распределение и т.д., применяется на практике."
"Задачи по программированию тоже очень полезны."
Well-explained content, great teacher
"Отличная подача материала, автор хорошо объясняет."
"Замечательный курс! Доступно объясняется..."
Easy-to-understand concepts
"Отличный курс! Спасибо!"
"Крутой курс как и сам лектор, все очень понятно и классно объясняет)"
"Большое спасибо автору курса за довольно подробное изложение информации, которую искать в разных источниках довольно трудно..."
Requires Python knowledge
"Входной порог обозначен на странице курса, но повторю: без знания Python на начальном уровне и основ теории вероятности брать курс не стоит."

Activities

Coming soon We're preparing activities for Сбор и анализ данных в Python. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Сбор и анализ данных в Python will develop knowledge and skills that may be useful to these careers:
Data Analyst
The online course Сбор и анализ данных в Python from HSE University can be a valuable resource for aspiring Data Analysts. This course provides a comprehensive overview of data analysis fundamentals, including data collection, processing, visualization, and descriptive statistics. By mastering these skills, learners can build a solid foundation for a successful career in data analysis.
Data Scientist
HSE University's Сбор и анализ данных в Python online course offers a solid foundation for individuals seeking a career as a Data Scientist. This course covers essential concepts in mathematical statistics, data collection, processing, and visualization. By gaining proficiency in these areas, learners can develop the analytical and problem-solving skills required to excel in data science.
Statistician
HSE University's Сбор и анализ данных в Python online course aligns well with the foundational knowledge required for a career as a Statistician. This course provides a comprehensive introduction to statistical principles and methods, including data collection, analysis, and visualization. By completing this course, learners can gain a strong understanding of statistical techniques and their applications in various fields.
Business Analyst
The Сбор и анализ данных в Python online course from HSE University can be beneficial for individuals pursuing a career as a Business Analyst. This course offers a practical approach to data analysis, focusing on data collection, processing, and visualization. By mastering these skills, learners can develop the analytical capabilities and data-driven insights necessary for success in business analysis.
Data Engineer
HSE University's Сбор и анализ данных в Python online course provides a valuable foundation for individuals interested in becoming Data Engineers. This course introduces the basics of data collection, processing, and visualization, equipping learners with the essential skills to manage and analyze large datasets. By completing this course, aspiring Data Engineers can gain a strong understanding of data engineering principles and practices.
Quantitative Analyst
The Сбор и анализ данных в Python online course offered by HSE University can be a valuable resource for those aspiring to become Quantitative Analysts. This course provides a solid foundation in data analysis techniques, including data collection, processing, and visualization. By mastering these skills, learners can develop the analytical capabilities and problem-solving mindset required for success in quantitative analysis.
Actuary
The Сбор и анализ данных в Python online course from HSE University may be helpful for individuals considering a career as an Actuary. This course provides an introduction to statistical principles and methods, including data collection and analysis. By completing this course, aspiring Actuaries can gain a better understanding of statistical concepts and their applications in the insurance industry.
Market Researcher
HSE University's Сбор и анализ данных в Python online course can be beneficial for individuals seeking a career in Market Research. This course covers essential data analysis techniques, including data collection, processing, and visualization. By mastering these skills, learners can develop the analytical capabilities and insights necessary to conduct effective market research and inform business decisions.
Epidemiologist
The Сбор и анализ данных в Python online course offered by HSE University may be useful for individuals interested in pursuing a career as an Epidemiologist. This course provides an introduction to statistical methods and data analysis, which are essential for understanding and analyzing health-related data. By completing this course, aspiring Epidemiologists can gain a better understanding of statistical principles and their applications in the field of public health.
Biostatistician
HSE University's Сбор и анализ данных в Python online course may be helpful for individuals considering a career as a Biostatistician. This course provides an introduction to statistical principles and methods, including data collection and analysis. By completing this course, aspiring Biostatisticians can gain a better understanding of statistical concepts and their applications in the field of healthcare.
Data Visualization Specialist
The Сбор и анализ данных в Python online course offered by HSE University can be beneficial for individuals interested in a career as a Data Visualization Specialist. This course covers essential data visualization techniques, including data processing and visual representation. By mastering these skills, learners can develop the ability to create compelling and informative data visualizations that communicate insights effectively.
Research Analyst
HSE University's Сбор и анализ данных в Python online course may be useful for individuals considering a career as a Research Analyst. This course provides an introduction to data analysis techniques, including data collection, processing, and visualization. By completing this course, aspiring Research Analysts can gain a better understanding of how to analyze data to support research projects and inform decision-making.
Financial Analyst
The Сбор и анализ данных в Python online course offered by HSE University may be helpful for individuals interested in a career as a Financial Analyst. This course provides an introduction to data analysis techniques, including data collection, processing, and visualization. By completing this course, aspiring Financial Analysts can gain a better understanding of how to analyze financial data to support investment decisions and inform business strategies.
Software Engineer
HSE University's Сбор и анализ данных в Python online course may be helpful for individuals considering a career as a Software Engineer, particularly those interested in data-driven development. This course provides an introduction to data analysis techniques, including data collection, processing, and visualization. By completing this course, aspiring Software Engineers can gain a better understanding of how to use data to improve software design and functionality.
Product Manager
The Сбор и анализ данных в Python online course offered by HSE University may be beneficial for individuals interested in a career as a Product Manager. This course provides an introduction to data analysis techniques, including data collection, processing, and visualization. By completing this course, aspiring Product Managers can gain a better understanding of how to use data to inform product development and drive customer engagement.

Reading list

We've selected 14 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 Сбор и анализ данных в Python.
Provides a comprehensive introduction to probability and statistics, with a focus on applications in engineering and science. It covers the basics of probability, including probability distributions, conditional probability, and Bayes' theorem. It also covers the basics of statistics, including sampling, estimation, and hypothesis testing.
Provides a more advanced treatment of mathematical statistics, with a focus on data analysis. It covers the topics of probability distributions, statistical inference, and regression analysis.
Provides an introduction to data science, with a focus on business applications. It covers the topics of data collection, data cleaning, data analysis, and data visualization.
Provides a practical introduction to machine learning, with a focus on using Python libraries such as Scikit-Learn, Keras, and TensorFlow. It covers the topics of supervised learning, unsupervised learning, and deep learning.
Provides a comprehensive introduction to Python for data analysis. It covers the topics of data structures, data manipulation, data visualization, and machine learning.
Provides an introduction to statistics for data science. It covers the topics of probability, statistical inference, and regression analysis.
Provides a comprehensive introduction to deep learning. It covers the topics of neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive introduction to data mining. It covers a number of data mining algorithms such as decision trees and random forests.
Provides a comprehensive introduction to statistical learning. It covers a number of statistical learning algorithms such as linear regression and support vector machines.
Provides a comprehensive introduction to pattern recognition and machine learning. It covers a number of pattern recognition and machine learning algorithms such as neural networks and support vector machines.
Provides a comprehensive introduction to reinforcement learning. It covers a number of reinforcement learning algorithms such as Q-learning and SARSA.
Provides a comprehensive introduction to statistical methods for data analysis. It covers a number of statistical methods such as regression analysis and analysis of variance.

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