CST 383: Introduction to Data Science

Learned how to use data analysis and machine learning to visualize data, identify trends, and make predictions. Covered how to collect and preprocess data, apply machine learning methods, and visualize results. Built both the theoretical knowledge and practical programming skills needed to carry out complete data science projects using modern statistical languages and libraries. For example, I worked with NumPy arrays, slicing, fancy indexing, and boolean masks to filter and manipulate data. I also used Pandas to compute averages, medians, and other summary statistics, and created plots such as histograms, density plots, box plots, and cumulative density plots to explore distributions. In addition, I practiced analyzing real datasets like college statistics and campaign contributions, which helped me understand how to clean data, compare groups, and interpret patterns in a meaningful way.