Description
This is the final course in the IBM Data Science Professional Certificate as well as the Applied Data Science with Python Specialization. This capstone project course will give you the chance to practice the work that data scientists do in real life when working with datasets.
In this course you will assume the role of a Data Scientist working for a startup intending to compete with SpaceX, and in the process follow the Data Science methodology involving data collection, data wrangling, exploratory data analysis, data visualization, model development, model evaluation, and reporting your results to stakeholders.
You will be tasked with predicting if the first stage of the SpaceX Falcon 9 rocket will land successfully. With the help of your Data Science findings and models, the competing startup you have been hired by can make more informed bids against SpaceX for a rocket launch.
In this course, there will not be much new learning, instead you’ll focus on hands-on work to demonstrate and apply what you have learnt in previous courses. By successfully completing this Capstone you will have added a project to your data science and machine learning portfolio to showcase to employers.
What you will learn
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.
