This course (The English copy of "用Python玩转数据" <https://www.coursera.org/learn/hipython/home/welcome>) is mainly for non-computer majors. It starts with the basic syntax of Python, to how to acquire data in Python locally and from network, to how to present data, then to how to conduct basic and advanced statistic analysis and visualization of data, and finally to how to design a simple GUI to present and process data, advancing level by level.
от партнера
Data Processing Using Python
Нанкинский университет
Об этом курсе
Недавно просмотрено: 28,670
Приобретаемые навыки
Python ProgrammingNumpyPandasWxpython
100% онлайн
Начните сейчас и учитесь по собственному графику.
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Начальный уровень
Прибл. 28 часа на выполнение
Английский
Субтитры: Английский
от партнера
Нанкинский университет
Nanjing University (NJU) is committed to excellence in teaching and research. Located on the prosperous eastern coast of China, NJU provides a dynamic environment that nurtures learning, creativity, and discovery on one of the most beautiful campuses in the country. Taking NJU's university offerings on Coursera will be a rewarding experience for learners from every corner of the world.
Программа курса: что вы изучите
24 минуты на завершение
Welcome to learn Data Processing Using Python!
Hi, guys, welcome to learn “Data Processing Using Python”(The English version of "用Python玩转数据", url is https://www.coursera.org/learn/hipython/home/welcome)!In this course, I tell in a manner that enables non-computer majors to understand how to utilize this simple and easy programming language – Python to rapidly acquire, express, analyze and present data based on SciPy, Requests, Beautiful Soup libraries etc. Many cases are provided to enable you to easily and happily learn how to use Python to process data in many fields. 【Nov 18, 2019 @ @ @ @ @ @ @ Hi, all! The content is planned to be updated in the last two months. This update is relatively large, including practical operation and explanation of Python based cases, vector operation and broadcast ideas of numpy package and common applications, multiple links of data exploration and preprocessing (including in module 4), data analysis and data mining cases based on pandas, some of which are directly modified on the original video Some of them are presented in the form of expanded videos, especially the newly recorded videos, which have a lot of content to say, take a long time, and will be a little hard to learn. I have completed all the updates on Dec 16, 2019. Thank you for your patience. I hope you will enjoy the new version.】
24 минуты на завершение
1 видео ((всего 4 мин.)), 2 материалов для самостоятельного изучения
1 видео
Promotion Video3мин
2 материала для самостоятельного изучения
Teaching Methods10мин
FAQ10мин
7 ч. на завершение
Basics of Python
Hi, guys, welcome to learn Module 01 “Basics of Python”! I’ll first guide you to have a glimpse of its simplicity for learning as well as elegance and robustness. Less is more: the author of Python must know this idea well. After learning this module, you can master the basic language structures, data types, basic operations, conditions, loops, functions and modules in Python. With them, we can write some useful programs!
7 ч. на завершение
16 видео ((всего 170 мин.)), 5 материалов для самостоятельного изучения, 3 тестов
16 видео
2 The First Python Program16мин
3 Basics of Python Syntax15мин
4 Data Types of Python9мин
5 Basic Operations of Python10мин
6 Functions, Modules and Packages of Python8мин
1.1 Extension: Build a Python Environment4мин
1 Conditions12мин
2 range5мин
3 Loops15мин
4 break, continue and else in Loops11мин
5 Self-defined Functions14мин
6 Recursion11мин
7 Scope of Variable4мин
A1: Standard Library Functions14мин
A2: Exceptions10мин
5 материала для самостоятельного изучения
1.1 Walk into Python slides10мин
1.1 References10мин
1.1 Programming exercises(Not Graded)10мин
1.2 Multi-dimensional View of Python slides10мин
1.2 Control structure & function exercises(9 questions)10мин
2 практического упражнения
Walk into Python quiz20мин
More About Python quiz24мин
4 ч. на завершение
Data Acquisition and Presentation
Welcome to learn Module 02 “Data Acquisition and Presentation”! After learning this module, you can master the modes of acquiring local data and network data in Python and use the basic and yet very powerful data structure sequence, string, list and tuple in Python to fast and effectively present data and simply process data.
4 ч. на завершение
10 видео ((всего 139 мин.)), 5 материалов для самостоятельного изучения, 1 тест
10 видео
2 Network Data Retrieval20мин
2.1 Extension: RE introduction16мин
2.1 Extension: Dynamic web crawling example5мин
1 Sequence8мин
2 String17мин
3 List14мин
4 Tuple7мин
2.2 Extension: IO&functional programming15мин
2.2 Extension: Mutable objects modify issue9мин
5 материала для самостоятельного изучения
2 Data Retrieval and Represent slides10мин
2.1 Internet Data Retrival Programming exercise(Not Graded)10мин
2.1 code snippets for reference only10мин
Sequence fuctions practice10мин
Sequences and Files Programming Exercise(8 questions)10мин
1 практическое упражнение
Data Acquisition and Presentation quiz30мин
3 ч. на завершение
Powerful Data Structures and Python Extension Libraries
Welcome to learn Module 03 “Powerful Data Structures and Python Extension Libraries”! Have you felt you are closer to using Python to process data? After learning this module, you can master the intermediate-level and advanced uses of Python: data structure dictionaries and sets. In some applications, they can be very convenient. What’s special here is that, you can also feel the charm of such concise and efficient data structures: ndarray, Series and DataFrame in the most famous and widely applied scientific computing package SciPy in Python.
3 ч. на завершение
9 видео ((всего 109 мин.)), 5 материалов для самостоятельного изучения, 1 тест
9 видео
2 Dictionary Use15мин
3 Set11мин
3.1 Extension: dict and set programming examples12мин
1 Extension Library SciPy6мин
2 ndarray18мин
3 Series7мин
4 DataFrame8мин
3.2 Extension: Common numpy applications16мин
5 материала для самостоятельного изучения
3 Powerful Data Structure and Software Ecosystem slides10мин
3.1 Programming exercise(Not Graded)10мин
3.1 Classic dict programming(1 question)10мин
3.2 Programming exercise for DataFrame(Not Graded)10мин
3.2 Modify the DataFrames10мин
1 практическое упражнение
Powerful Data Structures and Python Extension Libraries quiz28мин
10 ч. на завершение
Python Data Statistics and Mining
Welcome to learn Module 04 “Python data statistics and mining”! In this module, I will show you, over the entire process of data processing, the unique advantages of Python in data processing and analysis, and use many cases familiar to and loved by us to learn about and master methods and characteristics. After learning this module, you can preprocess the data and fast and effectively mine your desired or expected or unknown results from a large amount of data, and can also present those data in various images. In addition, the data statistics modes of all third party packages in Python are extraordinarily and surprisingly strong, but we, as average persons, can still understand and possess them.
10 ч. на завершение
12 видео ((всего 222 мин.)), 13 материалов для самостоятельного изучения, 3 тестов
12 видео
2 Fundamentals of Python Plotting23мин
3 Data Clean of Data Exploration and Preprocessing20мин
4 Data Transformation of Data Precessing22мин
5 Data Reduction of Data Preproccessing18мин
1 Basic Data Characteristics Analysis of Data Exploration24мин
2 Data Statistics and Analysis Based on pandas27мин
3 Cluster Analysis14мин
4 Aplications of Python into Science and Engineering Fields7мин
5 Applications into Humanities and Social Sciences Fields7мин
4.2 Extension: An Analysis of the Differences between Males and Females on Film Ratings17мин
4.2 Extension: Classification of Red Wine Data Based on Random Forest Model21мин
13 материала для самостоятельного изучения
4.1 Data retrieval and preprocessing of Python Slides10мин
4.1 References10мин
4.1.1 code snippets for reference only10мин
4.1.3: Analyze test results using Box-plot10мин
Web API - TuShare and Data Analysis ta30мин
4.1 Titanic Data Set Acquisition10мин
4.2 Data Statistics, Mining and Application Slides10мин
4.2 code snippets for reference only10мин
4.2.1 K-means algorithm an discussion on K value10мин
4.2.1 Extension: Scikit-learn Machine Learning Basics10мин
4.2.6 Project- —Linear Regression for Boston houses price prediction10мин
4.2.6 Extension: Introduction to WAV audio processing10мин
4.2.7 Learn More about NLTK10мин
2 практического упражнения
Data retrieval and preprocessing of Python quiz16мин
Data Statistics, Mining and Application quiz20мин
4.3
Рецензии: 42Лучшие отзывы о курсе Data Processing Using Python
The course provides an insight into the basic structure of Python. It will help you in navigating the areas where Python is robust and effective.
It's a basic Python lesson, but providing some data analysis and GUI concepts, which needs you to explore after this class or in the future.
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Зарегистрировавшись на сертификацию, вы получите доступ ко всем видео, тестам и заданиям по программированию (если они предусмотрены). Задания по взаимной оценке сокурсниками можно сдавать и проверять только после начала сессии. Если вы проходите курс без оплаты, некоторые задания могут быть недоступны.
Что я получу, оплатив сертификацию?
Оплатив сертификацию, вы получите доступ ко всем материалам курса, включая оцениваемые задания. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.
Какие правила возврата средств?
Можно ли получить финансовую помощь?
Остались вопросы? Посетите Центр поддержки учащихся.