In “Python Debugging: A Systematic Approach,” you will develop essential coding skills for data science, focusing on writing, testing, and debugging code. You will learn foundational Python concepts, such as looping, control structures, variables, and basic debugging techniques. You will also learn how a structured debugging procedure can help you debug more effectively and efficiently.
Python Debugging: A Systematic Approach
Python Debugging: A Systematic Approach
This course is part of Data-Oriented Python Programming and Debugging Specialization
Instructors: Elle O'Brien
Included with 
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
20 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Use Jupyter Notebook to implement basic Python workflows and constructs.
Apply the OILER framework for debugging many common Python bugs.
Use official Python documentation to enhance understanding of different programming formats.
Interpret Python error messages to resolve runtime execution issues.
Details to know
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Recently updated!
March 2025
Assessments
2 assignments
Taught in English
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This course is part of the Data-Oriented Python Programming and Debugging Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
What's included
4 videos4 readings1 programming assignment1 discussion prompt2 ungraded labs
What's included
8 videos1 reading1 assignment1 programming assignment2 ungraded labs
What's included
6 videos1 reading1 programming assignment3 ungraded labs
What's included
5 videos3 readings1 assignment1 programming assignment1 ungraded lab
Offered by
Recommended if you're interested in Data Analysis
Microsoft
University of Michigan
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