- Type Validation
- Level Foundational
Data Analysis in Python
Earners of this credential build on knowledge obtained from the Intro to Python credential. The course covers many applications within Python that are relevant to data science. At the end of the credentialing program, participants will have an intermediate mastery of Python programming skills. Users will gain experience using Python to read in datasets for analysis, analyze their data using an array of statistical and data science tools, and create visual representations of their data.
- Type Validation
- Level Foundational
Skills
- Analysis Of Variance (ANOVA)
- ANOVA
- Chi-square
- Data Science
- Datasets
- Data Visualization
- Linear Regression
- Matplotlib Library
- Pandas Module
- Pandas (Python Package)
- Python
- Python (Programming Language)
- Researchpy Module
- SciPy
- Scipy Module
- Seaborn
- Seaborn Module
- Statistics
- Statistics Module
- Summary Calculations
- Time-series
- Time Series
- T-tests
Earning Criteria
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Earners of the digital badge completed: Obj 1 – Coding Project 1 (F) (pandas) Obj 1, 2 – Coding Project 2 (F) (t-tests, scipy module, statistics module) Obj 1, 2 – Coding Project 3 (S) (ANOVA, linear regression, time-series, chi-square, scipy, statistics module, seaborn module, pandas module, researchpy) Obj 1, 3 – Coding Project 4 (S) (data visualization, matplot library) . A minimum score of 80% was required on all assessments.