Data Collection and Processing with Python
Skills:
ML Pipelines70%
Key Takeaways
Covers data collection and processing with Python, including list comprehensions, REST APIs, and data extraction
Original Description
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.
Watch on External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: ML Pipelines
View skill →Related Reads
📰
📰
📰
📰
Presentation: Practical Robustness: Going Beyond Memory Safety in Rust
InfoQ AI/ML
Integration Digest for June 2026
Dev.to · Stanislav Deviatov
Decoupling Async State from UI Lifecycles
Dev.to · Luciano0322
Sentinel Promoted Three Times in Ten Minutes. Your App Read Stale Data Twice.
Medium · Programming
🎓
Tutor Explanation
DeepCamp AI