Структуры данных Python from Coursera

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Syllabus

Глава 6. Строки

В этом модуле мы вспомним, на чем остановились в последний раз; начнем с главы 6 учебника, поговорим о строках, а затем перейдем к структурам данных. На второй неделе данного курса мы займемся установкой среды языка Python, если вы захотите выполнять приложения на своем ПК или ноутбуке. Если вы не собираетесь устанавливать Python, можете перейти на неделю 3 и получить некоторую фору по времени.

Модуль. Установка и использование Python

В этом модуле будет предоставлена информация, на основании которой вы сможете создавать программы на Python. Устанавливать Python для этого курса не обязательно. Программы на Python можно создавать и тестировать в браузере с помощью подсистемы «Python Code Playground» на этом уроке. Более подробную информацию см. в разделе «Использование Python в этом курсе».

Глава 7. Файлы

До настоящего времени мы работали с данными, которые вводит пользователь, или с данными в константах. Однако реальные программы обрабатывают намного большие объемы данных путем считывания и записи файлов во вторичную память на компьютере. В этой главе мы начнем создавать наши первые программы, которые выполняют чтение, сканирование и обработку реальных данных.

Глава 8. Списки

Так как мы хотим решать более сложные задачи в среде Python, нам требуются более мощные переменные. До настоящего времени мы использовали простые переменные для хранения чисел или строк, когда в переменной есть одно значение. Благодаря применению списков мы будем хранить в одной переменной несколько значений, используя схему индексации для хранения, упорядочения и отыскания разных значений в этой переменной. Такие многозначные переменные мы называем «коллекциями» или «структурами данных».

Глава 9. Словари

Словарь Python является одной из самых мощных структур данных этого языка. Вместо представления значений в линейном списке, данные в словарях хранятся в виде пар «ключ-значение». Благодаря использованию пар «ключ/значение» мы получаем простую «базу данных» внутри памяти в одной переменной Python.

Глава 10. Кортежи

Кортежи являются нашей третьей и последней основной структурой данных Python. Кортежи представляют собой простую версию списков. Мы часто используем кортежи вместе со словарями для выполнения многоэтапных задач, например, для сортировки или закольцованного прохода через все данные в словаре.

Окончание курса

Чтобы отпраздновать достижение экватора в нашей специализации «Python для всех», приглашаем вас принять участие в церемонии окончания курса в режиме онлайн. Церемония не займет много времени. На ней с краткой поздравительной речью выступит сотрудник, отвечающий за вручение дипломов.

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Обучение основам процедурного программирования Python

Использование структур данных Python, таких как списки, словари и кортежи

Развитие навыков анализа данных с использованием структур данных Python

Материал соответствует главам 6-10 учебника «Python для всех»

Охватываются основы языка Python 3

Reviews summary

Python data structures

This course explores Python 3 data structures like lists, dictionaries, and tuples. Students learn how to analyze data using these structures and how to implement them in Python programs. Topics include strings, files, and tuples.

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 Структуры данных Python with these activities:

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Career center

Learners who complete Структуры данных Python will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts use their knowledge of Python data structures to collect, clean, and analyze large datasets. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective data analysis programs.

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Machine Learning Engineer

Machine Learning Engineers use their knowledge of Python data structures to develop and deploy machine learning models. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective machine learning programs.

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Data Scientist

Data Scientists use their knowledge of Python data structures to build machine learning models and predictive analytics applications. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective data science programs.

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Data Engineer

Data Engineers use their knowledge of Python data structures to design, build, and maintain data pipelines. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective data pipelines.

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Web Developer

Web Developers use their knowledge of Python data structures to design, develop, and maintain web applications. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective web applications.

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Software Engineer

Software Engineers use their knowledge of Python data structures to design, develop, and maintain software applications. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective software programs.

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Database Administrator

Database Administrators use their knowledge of Python data structures to design, implement, and maintain databases. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective database management programs.

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Financial Analyst

Financial Analysts use their knowledge of Python data structures to analyze financial data and make investment recommendations. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective financial analysis programs.

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Business Analyst

Business Analysts use their knowledge of Python data structures to analyze business data and make recommendations for improvement. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective business analysis programs.

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Statistician

Statisticians use their knowledge of Python data structures to analyze data and draw conclusions. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective statistical analysis programs.

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Operations Research Analyst

Operations Research Analysts use their knowledge of Python data structures to analyze data and make recommendations for improvement. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective operations research programs.

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Risk Analyst

Risk Analysts use their knowledge of Python data structures to analyze data and identify risks. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective risk analysis programs.

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Actuary

Actuaries use their knowledge of Python data structures to analyze data and calculate risks. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective actuarial programs.

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Quantitative Analyst

Quantitative Analysts use their knowledge of Python data structures to analyze data and make investment recommendations. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective quantitative analysis programs.

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Investment Analyst

Investment Analysts use their knowledge of Python data structures to analyze data and make investment recommendations. This course provides a solid foundation in Python data structures, which are essential for success in this role. You will learn how to use Python lists, dictionaries, and tuples to store, organize, and manipulate data. This knowledge will help you to write efficient and effective investment analysis programs.

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