Foundations of Python 2: Working with Data
Issued by
University of Cincinnati
This micro-credential is awarded by the University of Cincinnati Libraries in partnership with the College of Engineering and Applied Science. Learners explore Python data analysis with Pandas to manipulate dataframes via slicing, indexing, and querying. Learners apply statistical and aggregation methods to analyze datasets, create visualizations with matplotlib, Pandas, and seaborn, and build understanding of linear regression models for prediction with NumPy, scikit-learn, and statsmodels.
- Type Validation
- Level Foundational
- Time Hours
- Cost Free
Skills
Earning Criteria
-
Complete a comprehensive Canvas course featuring instructional videos and knowledge-check quizzes while working through hands-on Jupyter notebook exercises.
-
Demonstrate competency by successfully completing all module assessments covering data manipulation with Pandas, statistical analysis techniques, data visualization creation, and regression modeling implementation. Participants apply learned concepts through practical coding exercises in Google Colab.