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The final project "Applied Data Science Capstone: SpaceX" by IBM analyzed and visualized SpaceX's space launch data. It applied data science techniques, identified patterns, analyzed variables, and predicted successful landings. It included interactive visualizations and graphs to obtain valuable insights.

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Applied-Data-Science-Capstone-SpaceX

The final project "Applied Data Science Capstone: SpaceX" by IBM analyzed and visualized SpaceX's space launch data. It applied data science techniques, identified patterns, analyzed variables, and predicted successful landings. It included interactive visualizations and graphs to obtain valuable insights.

Introduction

SpaceX is a groundbreaking company that has revolutionized the space industry by offering rocket launches, particularly Falcon 9, at significantly lower prices, starting at 62 million dollars. In contrast, other providers charge upwards of 165 million dollars per launch. SpaceX has achieved remarkable cost savings by implementing the innovative concept of reusing the first stage of the rocket, enabling it to be landed and used again for future missions. By continuously refining this process, SpaceX aims to further reduce launch costs. As a data scientist working for a startup competing with SpaceX, the objective of this project is to develop a machine learning pipeline to predict the outcome of the first stage landing in future missions. This project is crucial in determining the optimal pricing strategy to compete with SpaceX for rocket launches.

Table of Contents

  1. Data Collection with API
  2. Data Collection with Web Scraping
  3. Data Wrangling
  4. EDA with SQL
  5. EDA with Visualization
  6. Interactive Visual Analytics with Folium
  7. Dashboard Application - (Code)
  8. Predictive Analysis - Machine Learning
  9. Technical presentation - (Slide)

Acknowledgements

© Bladimir Garcia, Republica Dominicana

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The final project "Applied Data Science Capstone: SpaceX" by IBM analyzed and visualized SpaceX's space launch data. It applied data science techniques, identified patterns, analyzed variables, and predicted successful landings. It included interactive visualizations and graphs to obtain valuable insights.

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