Data Processing Using Python from Coursera

This course (The English copy of "用Python玩转数据" ) 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.

This course, as a whole, based on Finance data and through the establishment of popular cases one after another, enables learners to more vividly feel the simplicity, elegance, and robustness of Python. Also, it discusses the fast, convenient and efficient data processing capacity of Python in humanities and social sciences fields like literature, sociology and journalism and science and engineering fields like mathematics and biology, in addition to business fields. Similarly, it may also be flexibly applied into other fields.

The course has been updated. Updates in the new version are :

1) the whole course has moved from Python 2.x to Python 3.x

2) Added manual webpage fetching and parsing. Web API is also added.

3) Improve the content order and enrich details of some content especially for some practice projects.

Note: videos are in Chinese (Simplified) with English subtitles. All other materials are in English.

What's inside

Syllabus

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.

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!

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.

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.

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.

Object Orientation and Graphical User Interface

Welcome to Module 05 “Object Orientation and Graphical User Interface”! In this module, I will guide you to understand what object orientation is and the relationship between graphical user interface and object orientation. Learners are only required to understand the concepts so that you can more freely and easily pick up various new functions in future. No program writing is required here. Besides, you also need to master the basic framework of GUI, common components and layout management. After learning them, you will find development with GUI is actually not remote.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Helps non-computer majors process data using Python

Covers data acquisition, presentation, analysis, and visualization

Uses Python libraries such as SciPy, Requests, and Beautiful Soup

Applicable to various fields, including business, humanities, and science

Instructors have experience in data processing

Reviews summary

Python-based data processing course

Learners say this course provides a solid introduction to data processing using Python. Its clear explanations, strong visuals, and engaging assignments are well received. However, it's important to note that the course is primarily in Mandarin, with limited English subtitles. This may pose a challenge for non-Mandarin speakers.

Regular assignments help reinforce learning and provide hands-on experience.

"Great course to learn python data processing. I think in week-4 need more details. Otherwise this course is fully enjoyable to me. Lots of learning is here. Thank you madam. Thank you university."

Zhang is praised for her clear explanations and engaging teaching style.

"This course cover Data Processing from A to Z, through excelent leacturer and great platform."

"If you are a newbie to Python, this is an excellent choice.The English subtitles and materials helped me a lot."

"Me Alegra mucho haber hecho este curso. Realmente fue mas que introductorio, la cantidad de herramientas que ofrece son muy poderosas, y el contenido lo suficientemente profundo. Zhang Dazhuang fue muy generosa enseñando, se lo agradezco. "

Provides a comprehensive overview of data processing concepts, with a focus on Python.

"It is a good course: it introduces the language and many interesting libraries."

"Great course with detailed and well-explained concepts. Sufficient examples."

"I am enjoying the course. The content is very interesting."

English subtitles are provided for most videos, but their quality can be inconsistent and may not cover all information.

"All the lectures should be given in English so that it will be helpful for students all over the world."

"If taken in English, reading subtitles can be a bit tough."

"Please be aware this course is completely in Chinese. If you are proficient in the language you can take full advantage of the course. Although there are translations to several languages available, it's really hard to keep the pace and fully get the whole information provided."

Course materials are mostly in Mandarin, despite being advertised as English.

"It's supposed to be translated to English however its not. It is still in Chinese language."

"The course is in Chinese language. So how the students will be able to learn and understand if they are not from china or don't have the knowledge of Chinese language?"

"The worst off-campus course I have ever had.First, the whole course was delivered by CHINESE."

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 Data Processing Using Python with these activities:

Review Python libraries for data analysis

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Ensure you are familiar with the key Python libraries used for data analysis, such as NumPy, Pandas, and Scikit-learn.

Browse courses on NumPy

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Review documentation or tutorials on these libraries.
Complete a few practice exercises using these libraries.

Create a data visualization dashboard

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Demonstrate your understanding of data visualization techniques by creating a dashboard that presents insights from a given dataset.

Browse courses on Data Visualization

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Choose a dataset that interests you.
Explore the data and identify key insights.
Design and create a dashboard using Python libraries like Matplotlib or Seaborn.
Present your dashboard to the class or a group of peers.

Create a Python data analysis tutorial

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Reinforce your understanding of Python data analysis techniques by creating a tutorial that explains a specific topic.

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Choose a specific topic within Python data analysis that you want to cover.
Research the topic thoroughly and gather resources.
Organize your content into a logical flow.
Create the tutorial using a platform like Medium or YouTube.
Share your tutorial with others and gather feedback.

Show all three activities

Career center

Learners who complete Data Processing Using Python will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists are in charge of collecting, interpreting, and presenting data to help businesses make better decisions. This course will be beneficial to your pursuit of this role by providing you with a strong understanding of the Python programming language and essential libraries like SciPy, Requests, and Beautiful Soup. You will learn to gather and organize data, explore and analyze it, and share your findings.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts use their technical prowess in data science to analyze data to discern patterns and relations. This course provides a strong foundational understanding of the syntax of Python, which is one of the most commonly used languages in data science. With course topics covering the acquisition, expression, analysis, and presentation of data, you will be well-equipped to handle the beginning phases of many data analysis tasks.

See salaries and explore the career path for Data Analyst

Data Science Manager

Data Science Managers oversee the development and execution of data science projects. This course can help you learn the basics of Python and essential libraries like SciPy and Pandas, which are widely used in data science. The course covers data acquisition, analysis, and visualization, all of which are important for managing data science projects.

See salaries and explore the career path for Data Science Manager

Statistician

Statisticians collect, analyze, interpret, and present data. This course can help you learn Python, which is frequently used in the field of statistics. The course covers data acquisition, analysis, and visualization, all of which are important for statistical analysis.

See salaries and explore the career path for Statistician

Data Visualization Specialist

Data Visualization Specialists create visual representations of data to help businesses understand and communicate their data. This course will teach you how to use Python to acquire and analyze data, and how to create clear and effective data visualizations.

See salaries and explore the career path for Data Visualization Specialist

Insurance Analyst

Insurance Analysts use data to analyze risks and determine insurance premiums. This course will provide you with a good foundation in Python, a programming language often used in insurance analysis. You will learn how to acquire, analyze, and present insurance data, and how to build and use insurance models.

See salaries and explore the career path for Insurance Analyst

Machine Learning Engineer

Machine Learning Engineers are specialists who design, develop, and deploy machine learning models. This course will teach you the basics of Python, a popular programming language used in the field of machine learning. You will also learn how to acquire, prepare, and analyze data, and how to build and evaluate machine learning models using Python.

See salaries and explore the career path for Machine Learning Engineer

Business Analyst

Business Analysts use data to help businesses make better decisions. This course will provide you with a solid foundation in Python, a popular programming language used in business analysis. You will learn how to acquire, analyze, and present data, as well as how to build and use data-driven models.

See salaries and explore the career path for Business Analyst

Financial Analyst

Financial Analysts use data to analyze financial performance and make investment recommendations. This course will provide you with a good foundation in Python, a programming language frequently used in financial analysis. You will learn how to acquire, analyze, and present financial data, and how to build and use financial models.

See salaries and explore the career path for Financial Analyst

Data Engineer

Data Engineers design, build, and maintain the infrastructure that stores and processes data. This course provides a good introduction to Python, a popular programming language used in data engineering. The course covers data acquisition and processing techniques, which are essential for data engineering.

See salaries and explore the career path for Data Engineer

Market Researcher

Market Researchers study consumer behavior and market trends to help businesses make better decisions. This course will provide you with a solid foundation in Python, a commonly used programming language in market research. You will learn how to acquire, analyze, and present data, and how to build and use data-driven models.

See salaries and explore the career path for Market Researcher

Software Engineer

Software Engineers design, develop, and maintain software applications. This course is a good start to learning Python, a commonly used programming language in software engineering. It provides a foundation in Python syntax, data acquisition, presentation, and debugging, which are important for software development.

See salaries and explore the career path for Software Engineer

Database Administrator

Database Administrators are responsible for managing and maintaining databases. This course provides a good foundation in Python, a programming language frequently used in database administration. The course covers data acquisition and processing techniques, which are essential for managing databases.

See salaries and explore the career path for Database Administrator

Epidemiologist

Epidemiologists study the causes and distribution of diseases in populations. This course can help you learn Python, which is sometimes used in epidemiology for data acquisition, analysis, and visualization. The course covers data acquisition techniques and basic data analysis methods, both of which are helpful for epidemiology research.

See salaries and explore the career path for Epidemiologist

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. This course can serve as an introduction to Python, which is widely used in the financial industry. The course covers data acquisition and presentation techniques that are essential for financial modeling.

See salaries and explore the career path for Quantitative Analyst