During my first-year internship, I worked in Python 3.12 using Jupyter Notebook to process and analyze biomechanical data. My main tasks involved data cleaning to ensure accuracy and consistency, followed by data aggregation to prepare the dataset for modeling. I then trained two machine learning models—a Random Forest and a Logistic Regression—with the goal of predicting pathologies based on biomechanical variables. This workflow allowed me to gain hands-on experience in data preprocessing, feature engineering, and model evaluation within a real-world biomedical context.

The data was real data: the internship was carried out at MySmartMove.