Welcome to my project repository for the UTSA Data Science & AI Community Innovation Scholars Program. Over the course of this 10-week internship, I'm working with real-world datasets and sharpening my Python, data analysis, and problem-solving skills to support community-focused nonprofits.
Each of these beginner-friendly Python scripts reflects key skills developed during the internship, such as logic building, algorithmic thinking, and basic data analysis.
A simple Python calculator script that performs basic arithmetic operations like addition, subtraction, multiplication, and division.
Generates the Fibonacci sequence up to a user-defined limit using a loop-based approach.
A quick tool to determine whether a given year is a leap year, based on logical conditions in Python.
A basic data analysis script using the Titanic dataset. Demonstrates data handling and exploration.
A machine learning project that predicts passenger survival on the Titanic using logistic regression. The workflow includes:
- Data preprocessing with pandas method chaining
- Handling missing values and encoding categorical variables
- Splitting data into training and testing sets (80/20 split)
- Training a logistic regression model using scikit-learn
- Evaluating model performance with accuracy score
Achieved an accuracy of approximately 77.5% on the test dataset.
- Python 3.x
- Jupyter Notebook or standard Python scripts
- pandas, NumPy
- scikit-learn
This repository is part of my work with the UTSA Data Science and AI Community Innovation Scholars Program, in collaboration with local nonprofits. The goal is to apply data science methods to support meaningful causes and build technical experience in the process, all while using private & public data, and artificial neural networks.
👩💻 Repo maintained by: Daniella Bowerman aka Dan
📍 Intern at: United Way San Antonio & Bexar County
🎓 B.S. Computer Science, Concentration in Cyber Ops
🎺 Member of UTSA Mariachi Los Paisanos