● Analyzed bike share data to determine how to convert casual riders into members. Used R to clean and transform the data, and Tableau to create dashboards to allow users to explore the visualized data.
● Analyzed data from the world health organization to visualize trends in COVID infections and vaccinations. Used Excel to format the data, created a database with Microsoft SQL SMS. I used MySQL to explore and transform the data, and Tableau to visualize the data.
● Used linear regression to develop models to predict the most profitable stocks in the S&P 500 using Python. Used data scraping techniques to retrieve data from Yahoo Finance.
● Used Python with Pandas and NumPy to find statistical correlations between different variables in movie box office revenue data, and visualize these correlations with Seaborn.
● Used SQL to clean and transform a dataset on Housing purchases in Nashville.
● Used Tableau to visualize Global CO2 emissions by country.