Sorry, this page is no longer available

We may earn an affiliate commission when you visit our partners.

Capstone

Retrieving, Processing, and Visualizing Data with Python

Charles Russell Severance

In the capstone, students will build a series of applications to retrieve, process and visualize data using Python. The projects will involve all the elements of the specialization. In the first part of the capstone, students will do some visualizations to become familiar with the technologies in use and then will pursue their own project to visualize some other data that they have or can find. Chapters 15 and 16 from the book “Python for Everybody” will serve as the backbone for the capstone. This course covers Python 3.

Enroll now

Or subscribe to Coursera Plus

And get unlimited access to Coursera

Here's a deal for you

Save money when you learn with a deal that may be relevant to this course.

All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

Valid until March 12, 2027

Save 40% Off 3 Months

Access thousands of top-rated learning programs with a Coursera Plus monthly subscription and take 40% off 3 months for a limited time.

What's inside

Syllabus

Welcome to the Capstone

Congratulations to everyone for making it this far. Before you begin, please view the Introduction video and read the Capstone Overview. The Course Resources section contains additional course-wide material that you may want to refer to in future weeks.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Explores the fundamentals of data visualization with Python, focusing on data retrieval, processing, and visualization techniques

Provides hands-on experience through projects that involve building a search engine, exploring data sources, and visualizing email data

Suitable for learners with prior experience in Python as covered in the earlier courses of the specialization

Taught by Charles Russell Severance, an expert in data science and visualization

Requires familiarity with Python 3 for effective participation

Utilizes an optional project for learners to apply their skills to a data source of their choice, fostering independent exploration

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.

Save

Reviews summary

Python capstone: data applications

According to learners, this capstone course is a highly rewarding culmination of the Python for Everybody specialization. Many found the hands-on projects and practical application of Python for data tasks like retrieval, processing, and visualization to be extremely valuable. The course structure, including optional projects and Honors assignments, is praised for providing flexibility and deeper engagement for those seeking it. While the material is considered a challenging yet fulfilling wrap-up, most students feel it effectively solidifies concepts from previous courses, providing actionable skills.

Offers flexibility for deeper study.

"The optional Honors assignments provide a chance to dig much deeper if you have time."

"Appreciate the flexibility of the personal project being optional but highly recommended."

"The course structure allows you to choose your level of engagement."

"Great having the option to do the extra work for more learning."

Demanding but provides significant learning.

"The course is challenging, especially the projects, but incredibly rewarding."

"Some parts felt difficult, requiring significant effort, but mastering them was satisfying."

"Definitely not easy, but the learning gained is substantial."

"Requires dedication, but the outcome is worth the hard work put in."

Effectively ties together prior learning.

"This course brings together all the knowledge from the previous courses very well."

"It's a perfect culmination of the Python for Everybody specialization."

"Really helped solidify my understanding of the concepts learned previously and apply them."

"Finally, seeing how all the pieces fit together for real applications was great."

Focuses on applicable data skills.

"I learned how to use practical tools and strategies that I could apply immediately to my work."

"Getting experience with APIs, databases, and visualization libraries is very relevant."

"The skills taught here are directly useful for data analysis tasks."

"This course equips you with actionable skills for retrieving, processing, and visualizing data."

Provides practical, real-world experience.

"The hands-on coding and projects are the strongest part of the course for me."

"I loved the project where I could find my own data set and work with it."

"Building a search engine and working with email data felt very practical and insightful."

"Learned a lot by actually building something end-to-end."

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 Capstone: Retrieving, Processing, and Visualizing Data with Python with these activities:

Review and Organize Course Resources

Show steps

Ensure a solid foundation for your learning by organizing and reviewing course materials before the course commences.

Show steps

Review the course syllabus and objectives
Download and skim through the assigned readings and resources
Organize your notes and study materials in a systematic manner

Review Statistics Concepts

Show steps

Revisit the fundamental principles of statistics, which are essential for understanding data analysis techniques.

Browse courses on Statistics

Show steps

Review lecture notes or online resources on basic statistics
Solve practice problems to test your understanding
Engage in discussion forums or study groups to clarify concepts

Review Python 3 Basics

Show steps

Reinforce your understanding of Python syntax, variables, and data types, which are essential for success in this course.

Browse courses on Python Syntax

Show steps

Review online resources for Python 3 fundamentals
Complete practice exercises on variables, data types, and operators
Take a practice quiz to assess your understanding

Five other activities

Expand to see all activities and additional details

Show all eight activities

Discussion on Data Sources

Show steps

Engage in peer discussions to broaden your understanding of data sources and their relevance to data analysis.

Browse courses on Data Sources

Show steps

Participate in online forums or discussion groups related to data sources
Organize a study group with peers to discuss different types of data sources and their applications
Share your own experiences and insights on data source identification and selection

Coding Exercises on Building Search Engines

Show steps

Enhance your coding proficiency in web crawling and scraping techniques, which are crucial for building search engines.

Browse courses on Web Crawling

Show steps

Find online coding challenges or platforms that offer exercises on building search engines
Attend a coding session or workshop on search engine development
Implement a mini-search engine using Python and compare its performance with existing search algorithms

Leveraging Data Visualization Tools

Show steps

Gain practical experience with data visualization techniques using Matplotlib and Seaborn, which are essential for presenting data insights.

Browse courses on Data Visualization

Show steps

Follow interactive tutorials on Matplotlib and Seaborn to learn the basics of data visualization
Explore online resources and documentation to discover advanced data visualization techniques
Create your own interactive data visualizations using real-world datasets

Visualizing Email Data

Show steps

Develop practical skills in using Python for data analysis and visualization, including text extraction and processing.

Browse courses on Data Visualization

Show steps

Collect and clean email data using Python and the provided scripts
Explore the data to identify patterns and trends
Visualize the data using techniques covered in the course

Contribute to Python Data Analysis Projects

Show steps

Gain hands-on experience in practical data analysis by contributing to open-source projects on GitHub.

Browse courses on Open Source

Show steps

Identify open-source projects related to Python data analysis
Review the project's documentation and codebase
Contribute to the project by fixing bugs, adding features, or improving documentation

Career center

Learners who complete Capstone: Retrieving, Processing, and Visualizing Data with Python will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists analyze large amounts of structured and unstructured data to extract meaningful insights, develop predictive models, and make data-driven decisions. This course provides a foundation in Python programming, data retrieval, processing, and visualization, all of which are essential skills for Data Scientists. By completing this course, you will gain a competitive edge in the job market and be well-equipped to contribute to data-driven decision-making in various industries.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts collect, clean, and interpret data to identify patterns, trends, and insights that can inform business decisions. This course provides a comprehensive overview of data retrieval, processing, and visualization techniques, which are fundamental skills for Data Analysts. By taking this course, you will develop the analytical and technical skills necessary to succeed in this role.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models to solve complex business problems. This course provides a solid foundation in Python programming, data processing, and visualization, which are essential skills for Machine Learning Engineers. By completing this course, you will gain the technical expertise and practical experience needed to build and implement machine learning solutions.

See salaries and explore the career path for Machine Learning Engineer

Software Engineer, Data

Software Engineers (Data) specialize in developing software solutions for data-intensive applications. This course provides a comprehensive overview of data retrieval, processing, and visualization techniques, which are essential for building data-driven applications. By taking this course, you will gain the technical skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Software Engineer, Data

Data Visualization Specialist

Data Visualization Specialists create visual representations of data to communicate insights and trends. This course provides a thorough foundation in data visualization techniques, using Python and other tools. By completing this course, you will develop the skills and knowledge necessary to effectively convey data-driven insights to a wide range of audiences.

See salaries and explore the career path for Data Visualization Specialist

Data Journalist

Data Journalists use data to tell stories and inform the public. This course provides a comprehensive overview of data retrieval, processing, and visualization techniques, which are essential for Data Journalists. By taking this course, you will gain the skills and knowledge necessary to uncover and communicate data-driven insights in a compelling and engaging way.

See salaries and explore the career path for Data Journalist

Business Analyst

Business Analysts use data to identify and solve business problems. This course provides a foundation in data retrieval, processing, and visualization, which are essential skills for Business Analysts. By completing this course, you will gain the analytical and technical skills necessary to succeed in this role.

See salaries and explore the career path for Business Analyst

Market Researcher

Market Researchers collect and analyze data to understand market trends and consumer behavior. This course provides a foundation in data retrieval, processing, and visualization, which are essential skills for Market Researchers. By completing this course, you will gain the analytical and technical skills necessary to succeed in this role.

See salaries and explore the career path for Market Researcher

Financial Analyst

Financial Analysts use data to evaluate and make recommendations on financial investments. This course provides a foundation in data retrieval, processing, and visualization, which are essential skills for Financial Analysts. By completing this course, you will gain the analytical and technical skills necessary to succeed in this role.

See salaries and explore the career path for Financial Analyst

Operations Research Analyst

Operations Research Analysts use data to improve the efficiency and effectiveness of operations. This course provides a foundation in data retrieval, processing, and visualization, which are essential skills for Operations Research Analysts. By completing this course, you will gain the analytical and technical skills necessary to succeed in this role.

See salaries and explore the career path for Operations Research Analyst

Statistician

Statisticians collect, analyze, and interpret data to draw conclusions about populations. This course provides a foundation in data retrieval, processing, and visualization, which are essential skills for Statisticians. By completing this course, you will gain the analytical and technical skills necessary to succeed in this role.

See salaries and explore the career path for Statistician

Epidemiologist

Epidemiologists investigate the causes and patterns of disease in populations. This course provides a foundation in data retrieval, processing, and visualization, which are essential skills for Epidemiologists. By completing this course, you will gain the analytical and technical skills necessary to succeed in this role.

See salaries and explore the career path for Epidemiologist

Biostatistician

Biostatisticians apply statistical methods to solve problems in biology and medicine. This course provides a foundation in data retrieval, processing, and visualization, which are essential skills for Biostatisticians. By completing this course, you will gain the analytical and technical skills necessary to succeed in this role.

See salaries and explore the career path for Biostatistician

Computer Scientist

Computer Scientists design and develop computer systems and applications. This course provides a foundation in Python programming, data retrieval, processing, and visualization, which are essential skills for Computer Scientists. By completing this course, you will gain the technical skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Computer Scientist

Software Engineer

Software Engineers design, develop, and maintain software systems. This course provides a foundation in Python programming, data retrieval, processing, and visualization, which are essential skills for Software Engineers. By completing this course, you will gain the technical skills and knowledge necessary to succeed in this role.

See salaries and explore the career path for Software Engineer

Featured in The Course Notes

This course is mentioned in our blog, The Course Notes. Read one article that features Capstone: Retrieving, Processing, and Visualizing Data with Python:

5 New Specializations that Teach You Future-Proof Skills

7 minute read

Reading list

We've selected 23 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 Capstone: Retrieving, Processing, and Visualizing Data with Python.

Python for Everybody

Save

Is the backbone for the capstone of the course, and covers Python 3.

Capstone

Retrieving, Processing, and Visualizing Data with Python

Here's a deal for you

What's inside

Syllabus

Traffic lights

Save this course

Reviews summary

Python capstone: data applications

Activities

Career center

Featured in The Course Notes

Reading list

Share

Similar courses

Coursera Buyer Protection & Guarantee

7-Day Free Trial & Free Audit

14-Day Refund Guarantee

Verified Academic & Industry Partner