This project was completed as part of the IBM Data Science Certification course. It focuses on predicting the success of SpaceX Falcon 9 first stage landings, which has significant implications for launch cost estimation in the space industry.
- The project deals with predicting SpaceX Falcon 9 first stage landing success
- SpaceX launches cost $62M compared to competitors' $165M+
- Accurate prediction enables precise cost estimation
- This project will be valuable for competitors and launch service clients
- How to estimate launch costs by predicting first stage landing success?
- What is the optimal location for rocket launches?
- Data gathering via web scraping and SpaceX API
- Exploratory Data Analysis (EDA), encompassing:
- Data cleaning and preparation
- Visualization techniques
- Interactive visual analytics
- Predictive modeling using machine learning
- Successfully extracted valuable information from public sources
- EDA revealed the most predictive features for launch success
- Machine learning models identified crucial factors for optimal launch outcomes, utilizing the full dataset
This project demonstrates the application of data science techniques to a real-world problem in the space industry. By analyzing and predicting the success of Falcon 9 first stage landings, we contribute to the understanding of factors influencing launch costs and outcomes. This knowledge is not only valuable for SpaceX but also for competitors and clients in the launch service market.
The skills and methodologies employed in this project, including data collection, exploratory data analysis, and machine learning, are fundamental to the IBM Data Science Certification course. Through this project, we've applied these skills to a complex and impactful real-world scenario, showcasing the practical applications of data science in the aerospace industry.