Healthcare Cost Predictor: A Data Science Web Application

In the fast-evolving field of healthcare analytics, accurately predicting patient costs is vital for effective resource management and enhancing patient outcomes. In this project, you'll take on the role of a Data Scientist to develop a machine learning model that predicts healthcare costs using patient demographics and medical history. Guided by an experienced Build Fellow, you'll work on analyzing and preprocessing healthcare datasets, implementing a machine learning model, and deploying it as a predictive web application. The project guides you through a complete end-to-end workflow: starting with an existing healthcare dataset, performing data analysis and preprocessing, building prediction models.

You'll gain hands-on experience with data science essential tools and techniques like Python, Scikit-learn, Streamlit, and data visualization libraries, all while working in an environment that mirrors the workflow of a data science professional.