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Data-Oriented Python Programming and Debugging

Description

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.

  • Subject

  • Language

    English

  • Duration

    16 weeks

  • Status

    Available

  • U-M Credit Eligible

    No

Instructors

  • Elle O'Brien

    Lecturer IV and Research Investigator

    University of Michigan, School of Information

  • Paul Resnick

    Michael D. Cohen Collegiate Professor of Information

    University of Michigan, School of Information

  • Anthony Whyte

    Lecturer IV

    University of Michigan, School of Information

Courses (4)