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

Course image

Course image

Data Collection and Processing with Python

Course image

4.7

Based on 4,023 ratings

, see reviews

Paul Resnick

This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs. For the final project, you will construct a “tag recommender” for the flickr photo sharing site.

Read more

This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs. For the final project, you will construct a “tag recommender” for the flickr photo sharing site.

The course is well-suited for you if you have already taken the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). If you are already familiar with Python fundamentals but want practice at retrieving and processing complex nested data from Internet services, you can also benefit from this course without taking the previous two.

This is the third of five courses in the Python 3 Programming Specialization.

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

Nested Data and Nested Iteration

In week one the video lectures and activities from the Runestone textbook will cover more complex data structures. By the end of this week, you will have learned how to process json formatted data, traverse nested data using nested iteration, and extract values from nested data.

Read more

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Develops core Python skills for data fetching and processing from services on the Internet

Builds on prior courses in the 'Python 3 Programming Specialization' series

Introduces the Python requests module for interacting with REST APIs and API documentation

Emphasizes list comprehensions and provides opportunities to practice extracting and processing deeply nested data

Culminates in a practical project of building a tag recommender for Flickr

Save this course

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

Save

Reviews summary

Practical python data handling

According to learners, this course provides a solid and practical foundation in data collection and processing using Python. Students particularly appreciate the focus on nested data structures, list comprehensions, and utilizing the requests module for APIs. The hands-on coding and projects, especially the final project, are frequently highlighted as highly beneficial for solidifying understanding. While largely well-structured and clear, some learners note the pace can be fast or certain assignments challenging, occasionally requiring external searching. Overall, it's seen as a strong continuation for those in the specialization.

Some content may need updating.

"Some examples felt slightly dated, although the core concepts are still relevant."

"APIs covered were good but might benefit from more modern or diverse examples."

"Could use more coverage on complex data structures or error handling practices."

"Small parts seem a bit out of sync with the latest Python practices."

Builds well on prior Python courses.

"This course is a perfect follow-up to the first two courses in the specialization."

"Requires a solid understanding of Python fundamentals, as stated in the prerequisites."

"Good progression from the basics covered earlier, building more complex ideas."

"Fits well into the overall Python programming specialization path."

Explains complex topics clearly.

"The explanations of nested data and list comprehensions were very clear and helpful."

"Instructors did a good job breaking down the API concepts into manageable steps."

"Found the lectures easy to follow and the concepts well-explained."

"Good introduction to how to handle JSON data effectively."

Builds practical data handling skills.

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

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

"The final project was challenging but really helped solidify the concepts."

"Applied skills are key here, and the exercises deliver."

Assignments can be tricky.

"Assignments sometimes required searching outside the course materials for clarification."

"The labs were good practice but occasionally frustrating due to lack of hints."

"Wish there were more practice exercises before the graded assignments."

"Some assignment instructions could be clearer."

Can be challenging for some learners.

"Some sections, especially the API part, moved quite fast."

"Needed to spend extra time reviewing lectures and materials to keep up."

"Could be challenging without prior programming experience, even with the prerequisites."

"The learning curve felt steep at times."

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 Collection and Processing with Python with these activities:

Compile a list of useful resources for data extraction

Show steps

Create a valuable reference for yourself and others by organizing and expanding on the course materials on data extraction.

Browse courses on Python

Show steps

Review the course materials and identify key resources
Search for additional resources on the Internet, such as tutorials, articles, and tools
Organize the resources into a structured format, such as a document or website

Read 'Web Scraping with Python' by Ryan Mitchell

Show steps

Gain a comprehensive understanding of web scraping techniques and best practices.

View Web Scraping with Python: Data Extraction from... on Amazon

Show steps

Read through the book's chapters on data extraction and web scraping
Apply the concepts to your own web scraping projects

Practice using Python list comprehensions

Show steps

Refresh your understanding of Python list comprehensions to prepare for extracting and processing data from Internet services.

Browse courses on Python

Show steps

Review the syntax and usage of Python list comprehensions
Complete practice exercises involving extracting data using list comprehensions

Five other activities

Expand to see all activities and additional details

Show all eight activities

Follow online tutorials on using BeautifulSoup for web scraping

Show steps

Expand your data extraction skills by learning to use BeautifulSoup for web scraping.

Browse courses on BeautifulSoup

Show steps

Find reputable online tutorials on BeautifulSoup
Follow the tutorials and practice using BeautifulSoup
Apply your newfound knowledge to extract data from websites

Complete Python coding challenges related to data extraction

Show steps

Solidify your understanding of Python data extraction techniques through practice.

Browse courses on Data Extraction

Show steps

Find coding challenges that focus on data extraction
Attempt to solve the challenges using Python
Review solutions and learn from your mistakes

Contribute to open-source projects related to data extraction

Show steps

Gain practical experience and contribute to the community by volunteering on data extraction projects.

Browse courses on Open-Source

Show steps

Find open-source projects that focus on data extraction
Identify areas where you can make contributions
Collaborate with the project team and submit pull requests

Build a Python script to extract data from a specific API

Show steps

Apply your knowledge of Python and APIs to create a practical tool for extracting data from the Internet.

Browse courses on Data Extraction

Show steps

Identify an API that provides data relevant to your interests
Use Python's requests module to interact with the API
Extract the desired data and store it in a structured format
Test your script to ensure it retrieves data accurately

Participate in a hackathon focused on data extraction and analysis

Show steps

Challenge yourself and collaborate with others to apply your data extraction skills in a practical setting.

Show steps

Find a hackathon that aligns with your interests
Form a team or join an existing one
Develop a project proposal and build a solution involving data extraction
Present your project to a panel of judges

Career center

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

Data Scientist

Data Scientists leverage their extensive mathematical, coding, and statistical skills alongside knowledge of computer science, business, and industry-specific knowledge to find insights in data. This course's focus on data collection and processing with Python can be a useful addition to the skillset of a Data Scientist, who will likely be involved in all stages of the data pipeline including data collection, storage, and processing.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Closely related to Data Scientists, Machine Learning Engineers focus on developing and refining algorithms to advance machine learning models. Being well-versed in data collection, data processing, and working with nested data is essential for Machine Learning Engineers. Because this course covers these topics, it may be useful for working professionals looking to transition to the field of Machine Learning.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

Data Analysts work with data to collect, transform, and analyze it. The insights derived from this work are then used to make informed business decisions. Knowledge of data collection and processing are key for Data Analysts, and they may find the contents of this course helpful to expand their skills and knowledge in these areas.

See salaries and explore the career path for Data Analyst

Web Developer

Web Developers work with markup and programming languages to develop website functionality. This often includes integrating with external APIs to create features in the website. This course may be useful for Web Developers who wish to gain additional skills in data collection and processing from APIs.

See salaries and explore the career path for Web Developer

Software Engineer

Software Engineers build and design software applications. The knowledge and skills developed in this course, namely data collection and processing with Python, will be helpful for Software Engineers who may need to work with data from APIs in their projects.

See salaries and explore the career path for Software Engineer

Data Engineer

Data Engineers are responsible for the design, construction, and maintenance of data pipelines. This often includes work with data collection and processing. This course, therefore, may expand the skills of a Data Engineer and be useful in demonstrating competency.

See salaries and explore the career path for Data Engineer

Business Analyst

Business Analysts help companies understand how to improve their performance by leveraging data to identify opportunities. Much of the work that Business Analysts do requires data collection and processing skills. This course can be helpful for Business Analysts who wish to build upon these skills and apply them.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians collect, analyze, interpret, and present data. This work can require a strong understanding of data collection and processing, which this course covers in depth.

See salaries and explore the career path for Statistician

Research Analyst

Research Analysts conduct research to provide insights and make recommendations to clients. Data collection and processing skills are essential for Research Analysts, and this course can help to develop and refine these skills.

See salaries and explore the career path for Research Analyst

Database Administrator

Database Administrators ensure the smooth operation of databases. This often involves data collection and processing, skills that are covered in this course. Working professionals in this field may find this course useful for expanding their knowledge and skills in these areas.

See salaries and explore the career path for Database Administrator

UX Designer

UX Designers focus on improving the user experience of products and services. Data collection and processing skills can be useful for UX Designers who want to gain insights into user behavior. This course may be helpful for UX Designers who want to develop their skills in these areas.

See salaries and explore the career path for UX Designer

Information Security Analyst

Information Security Analysts plan and implement security measures to protect an organization's computer networks and systems. Data collection and processing skills may be useful for Information Security Analysts who need to collect and process data to identify and mitigate security risks.

See salaries and explore the career path for Information Security Analyst

Product Manager

Product Managers are responsible for the development and management of products. Data collection and processing skills can be useful for Product Managers who want to understand user behavior and make informed decisions about product development. This course may be helpful for Product Managers who want to build upon these skills.

See salaries and explore the career path for Product Manager

Financial Analyst

Financial Analysts make investment recommendations to individuals and organizations. They typically collect and process data to make these recommendations. This course can help to develop the data collection and processing skills that Financial Analysts need to succeed in this field.

See salaries and explore the career path for Financial Analyst

Market Research Analyst

Market Research Analysts gather and interpret data to understand consumer behavior. Data collection and processing skills are essential for Market Research Analysts. This course may be helpful for working professionals in this field to expand their knowledge and skills in these areas.

See salaries and explore the career path for Market Research Analyst

Reading list

We've selected nine 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 Data Collection and Processing with Python.

Cover image

Cover image

Dive Into Python

Save

This comprehensive guide to Python 3 provides in-depth coverage of the language's features and capabilities. It valuable resource for intermediate and advanced Python programmers.

Dive Into Python 3

Dive Into Python

Dive Into Python 3

Cover image

Cover image

A Million And One Random Digits

Save

Provides a concise and practical guide to the core principles of JavaScript. It must-read for anyone who wants to write clear and maintainable JavaScript code.

A Million And One Random Digits

A Million And One Random Digits

Cover image

Cover image

Python Pocket Reference

Save

Comprehensive and up-to-date guide to Python, providing valuable background and reference material for this course. It covers essential Python concepts, libraries, and tools and is commonly used as a textbook at academic institutions.

Python Pocket Reference

Python Pocket Reference

Cover image

Cover image

Python Cookbook

Save

This cookbook provides a collection of recipes for solving common Python programming problems. It serves as a valuable resource for finding quick solutions to specific challenges.

Python Cookbook: Recipes for Mastering Python 3

Python Cookbook (第3版) (中文版)

(Português) Python Cookbook

Cover image

Cover image

Python Crash Course, 3rd Edition

Save

Provides a practical and hands-on introduction to Python programming. It great resource for beginners who want to learn the basics of Python quickly.

Python Crash Course, 3rd Edition: A Hands-On,...

Python Crash Course, 3rd Edition: A Hands-On,...

Python Crash Course, 3rd Edition: A Hands-On,...

Python Crash Course, 3rd Edition: A Hands-On,...

Cover image

Cover image

Save

Provides a comprehensive overview of web APIs and how to use them with JavaScript. It valuable resource for front-end developers who want to learn more about web APIs.

DOM Scripting: Web Design with JavaScript and the...

Cover image

Cover image

Effective Python

Save

Covers best practices and idioms for writing efficient and maintainable Python code. It provides valuable insights and tips for Python programmers of all levels.

Effective Python: 90 Specific Ways to Write Better...

Effective Python: 59 Specific Ways to Write Better...

Effective Python: 90 Specific Ways to Write Better...

Effective Python: 59 Specific Ways to Write Better...

Cover image

Cover image

HTML5 and CSS3: Building Responsive Websites

Save

Provides a practical guide to creating responsive web designs that work well on all devices. It valuable resource for anyone who wants to design websites that are accessible to a wide range of users.

HTML5 and CSS3 Building Responsive Websites: One...

HTML5 and CSS3: Building Responsive Websites:...

Cover image

Cover image

JavaScript Pocket Reference

Save

This pocket reference provides a quick and easy way to look up jQuery syntax and functions. It useful tool for front-end developers who want to use jQuery in their web applications.

JavaScript Pocket Reference: Activate Your Web...

JavaScript Pocket Reference (2nd Edition)

JavaScript Pocket Reference

JavaScript Pocket Reference: Activate Your Web...

Share

Help others find this course page by sharing it with your friends and followers:

Copy Link

Similar courses

Here are nine courses similar to Data Collection and Processing with Python.

IoT Edge Computing: Amazon FreeRTOS Primer

IoT Edge Computing: Amazon FreeRTOS Primer

GenAI for DevOps Practitioners

GenAI for DevOps Practitioners

Data Balancing with Gen AI: Credit Card Fraud Detection

Data Balancing with Gen AI: Credit Card Fraud Detection

Harnessing Ollama – Create Local LLMs with Python

Harnessing Ollama – Create Local LLMs with Python

NLP – Machine Learning Models in Python

NLP – Machine Learning Models in Python

Programmatic Prompting with OpenAI: Refining and Filtering

Programmatic Prompting with OpenAI: Refining and Filtering

Meta Marketing Science Certification Exam

Meta Marketing Science Certification Exam

PyMongo - Advanced

PyMongo - Advanced

Optical Character Recognition (OCR) with Document AI (Python)

Optical Character Recognition (OCR) with Document AI...

Coursera Buyer Protection & Guarantee

Verified partner policies & purchase protections

Accredited University Partner

Free Trial & Audit

7-Day Free Trial & Free Audit

7-day free trial on monthly Coursera Plus subscriptions; free audit option available on most individual courses to explore video lectures and readings at no charge.

Return & Refund Policy

14-Day Refund Guarantee

14-day refund window on annual Coursera Plus subscriptions and single-course purchases prior to certificate issuance. Monthly subscriptions do not offer refunds once billed.

Buyer Protections

Verified Academic & Industry Partner

Accredited university and industry certifications (e.g. Stanford, Google, IBM, Yale), secure SSL payment processing, and verifiable digital certificate links.

Key Purchase Protections

14-day refund window on annual Coursera Plus and single courses

7-day free trial on monthly Coursera Plus subscriptions

Free course audit option for lectures and readings

Verified certificates from top universities & companies

OpenCourser Verified Partner Policy details last reviewed: 2026-10-22

Course image

Rating

4.7

Effort

Approx. 20 hours

Level

Intermediate

Via

Coursera

Institution

University of Michigan

Instructor

Paul Resnick

Language

English

Transcripts

Español Français Português Deutsch Italiano 中文 العربية 한국어 日本語 हिंदी Nederlands Svenska Pусский Türkçe Polski Ελληνικά українська мова magyar nyelv Bahasa Indonesia ไทย қазақша اُردُو, فارسی বাংলা tiếng Việt پښتو آذربایجان دیلی

This course belongs to a collection called Python 3 Programming. It's comprised of five courses:

Data Collection and Processing with Python (viewing)
Python Project: pillow, tesseract, and opencv
Python Classes and Inheritance
Python Functions, Files, and Dictionaries
Python Basics

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Develops core Python skills for data fetching and processing from services on the Internet

Builds on prior courses in the 'Python 3 Programming Specialization' series

Introduces the Python requests module for interacting with REST APIs and API documentation

Emphasizes list comprehensions and provides opportunities to practice extracting and processing deeply nested data

Culminates in a practical project of building a tag recommender for Flickr

Share this

Share to help others discover this course.

Link

Begin learning today

Enroll now to gain full access to Data Collection and Processing with Python.

Enroll now Enroll in this course

Save for later

Add this course to your list. Find it anytime.

Save

Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser