Data Analysis with Python and R

Data Analysis with Python and R introduces the knowledge and skills that students need to effectively make decisions using varied data sources. Students who complete this microcredential will have the ability to use the Python and R programming languages to create data visualizations, perform statistical analyses, and train machine learning models that yield actionable insights and support decision-making.

Competencies gained:

• Perform exploratory data analysis and visualization with Pandas, Plotly, and Bokeh
• Use Scikit-learn to train, validate, and apply machine learning models
• Automatically model and mine text documents using Tidy Text and spaCy
• Deploy visual data analytics dashboards using Streamlit and Heroku
• Use commercial data analysis platforms such as Google Analytics and Tableau

Take all of the following courses (12 credits):

• CMPSC 301 – Data Analytics

And take two of the following courses (8 credits):

• CMPSC 100 – Computational Expression
• CMPSC 101 – Data Abstraction
• CMPSC 102 – Discrete Structures

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