· Collected and structured real-time ocean environment data (e.g., water temperature, wave height, wind speed, air temperature) from public APIs. · Performed data cleaning with Pandas, including time normalization, unit conversion, and missing value handling. · Visualized environmental trends using Matplotlib by plotting time series line charts. · Built a feature engineering pipeline to extract indicators such as average daily wave height, temperature range, and air temperature gradient. · Trained dive site classification models using Scikit-learn (Logistic Regressiont) to categorize diving conditions into “Suitable”, “Moderate”, or “Unsuitable”. · Evaluated model performance via cross-validation and accuracy metrics; results were used to inform users about the comfort and difficulty levels of different dive sites.

This is my last quarter in College, try to find a data job