This project was completed as a part of the Honors portion of the Applied Data Science Capstone Course on Coursera.
Credit to IBM and the Coursera platform for providing the course materials and guidance.
The objective of this project is to assist SpaceY, a new company in the commercial rocket launch industry, to compete with SpaceX. SpaceX currently offers launch services at a starting price of $62 million, which includes some fuel reserved for landing the first stage rocket booster for reuse. By estimating the cost of building the first stage Falcon 9 booster (excluding R&D cost and profit margin) to be upwards of $15 million based on public statements made by SpaceX, the report aims to predict the successful landing of the first stage rocket booster with an 83.3% accuracy level using models based on mission parameters like payload mass and desired orbit. SpaceY intends to leverage these predictions to make informed bids against SpaceX, using them as a proxy for the cost of a launch and enhancing their competitive advantage.
- Data Collection API.ipynb
- Data Collection with Web Scraping.ipynb
- EDA.ipynb
- EDA with SQL.ipynb
- EDA with Visualization.ipynb
- Data Visualization with Folium.ipynb
- spacex_dash_app.py
- Machine Learning Prediction.ipynb
- spacex-booster-prediction-report.pdf