Сбор и анализ данных в Python from Coursera

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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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

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

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Сбор и анализ данных в Python with these activities:

Review Key Statistical Concepts

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Brushing up on key statistical concepts will help you hit the ground running when the course begins.

Browse courses on Statistics

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Review basic concepts of probability, such as events, sample spaces, and probability distributions.
Recall the definitions of statistical measures like mean, median, mode, variance, and standard deviation.
Refresh your understanding of hypothesis testing and confidence intervals.

Connect with a Mentor in the Field

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Finding a mentor can provide you with guidance and support throughout your learning journey.

Browse courses on Statistics

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Identify potential mentors through professional networks, conferences, or online platforms.
Reach out to potential mentors and express your interest in learning from them.

Read "An Introduction to Statistical Learning"

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This book provides a comprehensive overview of statistical learning methods, which will be essential for your understanding of the course material.

View An Introduction to Statistical Learning: with... on Amazon

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Read Chapters 1-3 to gain a foundation in supervised and unsupervised learning.
Work through the examples and exercises in the book to reinforce your understanding.

Four other activities

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Follow Online Tutorials on Statistics

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Online tutorials can provide additional support and clarification on the topics covered in the course.

Browse courses on Statistics

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Search for online tutorials on statistics using platforms like Coursera, edX, or YouTube.
Choose tutorials that cover specific topics you want to learn more about.
Follow the instructions and complete the exercises provided in the tutorials.

Solve Practice Problems on Probability and Statistics

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Regular practice will help you solidify your understanding of the concepts covered in the course.

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Find practice problems online or in textbooks.
Set aside time each week to work through the problems.
Check your answers to identify areas where you need more practice.

Participate in Study Groups

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Discussing the course material with peers can help you solidify your understanding and identify areas where you need more support.

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Form a study group with classmates.
Meet regularly to discuss the course material, work on assignments together, and quiz each other.

Create a Statistical Model

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Building a statistical model will give you hands-on experience applying the concepts you learn in the course.

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Choose a dataset and define a research question.
Explore the data and select appropriate statistical methods.
Build and evaluate the model.
Write a report summarizing your findings.

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.

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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.

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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.

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Business Analyst

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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.

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Quantitative Analyst

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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