Data-Oriented Python Programming and Debugging
About this course
In “Data-Oriented Python Programming and Debugging,” you will develop Python debugging skills and learn best practices, helping you become a better data-oriented programmer. Courses in the series will explore how to write and debug code, as well as manipulate and analyze data using Python’s NumPy, pandas, and SciPy libraries. You’ll rely on the OILER framework – Orient, Investigate, Locate, Experiment, and Reflect – to systematically approach debugging and ensure your code is readable and reproducible, ensuring you produce high-quality code in all of your projects. The series concludes with a capstone project, where you’ll use these skills to debug and analyze a real-world data set, showcasing your skills in data manipulation, statistical analysis, and scientific computing.
83/100
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- What the provider tells you
- 32/45
- Who stands behind it
- 35/35
- How complete the listing is
- 16/20
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What you'll learn
- develop debugging skills in Python
- learn to write and debug code effectively
- manipulate and analyze data using NumPy, pandas, and SciPy
- apply the OILER framework for systematic debugging
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