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Arizona State University vía Coursera
GRATIS

Applied Data Science Capstone

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  • Introduction
    • In this capstone, we will predict if the Falcon 9 first stage will land successfully. SpaceX advertises Falcon 9 rocket launches on its website, with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is because SpaceX can reuse the first stage. Therefore if we can determine if the first stage will land, we can determine the cost of a launch. This information can be used if an alternate company wants to bid against SpaceX for a rocket launch. In this module, you will be provided with an overview of the problem and the tools you need to complete the course.
  • Exploratory Data Analysis (EDA)
    • In this module, you will collect data on the Falcon 9 first-stage landings. You will use a RESTful API and web scraping. You will also convert the data into a dataframe and then perform some data wrangling.
  • Interactive Visual Analytics and Dashboard
    • In this module, you will build a dashboard to analyze launch records interactively with Plotly Dash. You will then build an interactive map to analyze the launch site proximity with Folium.
  • Predictive Analysis (Classification)
    • In this module, you will use machine learning to determine if the first stage of Falcon 9 will land successfully. You will split your data into training data and test data to find the best Hyperparameter for SVM, Classification Trees, and Logistic Regression. Then find the method that performs best using test data.
  • Present Your Data-Driven Insights
    • In this module, you will compile all of your activities into one place and deliver your data-driven insights to determine if the first stage of Falcon 9 will land successfully.