This is a repository for [the Applied Data Science Capstone] project offered by IBM and Coursera. This repository hosts the Notebooks and a Python file that I have worked on to run and complete the project. Huge thanks to IBM and Coursera for providing this learning opportunity.
Welcome to my repository for the capstone project of the IBM Data Science Professional Certificate, offered through Coursera. This repository contains the Jupyter notebooks and Python scripts that I developed to complete this capstone project.
This capstone project provided an opportunity to apply the data science skills I acquired during the IBM Data Science Professional Certificate program. I am grateful to IBM and Coursera for creating such a comprehensive learning experience.
SpaceX has a competitive advantage in space launch contracts due to its ability to land and reuse the first stage of the Falcon 9 rocket, drastically reducing launch costs. As a data scientist, predicting the success of these landings can offer valuable insights into overall launch costs, a critical aspect for companies bidding against SpaceX. Details on the specific problem statement, methodology, and results can be found within the notebooks.
One of the notebooks, Notebook6, features interactive maps created using the Folium library. Due to rendering issues on GitHub, the interactive maps may not be visible when viewing the notebook directly in this repository. To view these maps, please follow this link. Replace your link here with the actual link to view the interactive map.
Feel free to connect with me on LinkedIn.