Applied Data Science Capstone

Instructor: Yan Luo , Joseph Santarcangelo

Intermediate Level • 9 hours to complete • Flexible Schedule

What You'll Learn

  • Demonstrate proficiency in data science and machine learning techniques using a real-world data set and prepare a report for stakeholders
  • Apply your skills to perform data collection, data wrangling, exploratory data analysis, data visualization model development, and model evaluation
  • Write Python code to create machine learning models including support vector machines, decision tree classifiers, and k-nearest neighbors
  • Evaluate the results of machine learning models for predictive analysis, compare their strengths and weaknesses and identify the optimal model

Skills You'll Gain

Data analysis
Data-Driven Decision-Making
Data Collection
Statistical Modeling
Web Scraping
Data Wrangling
Predictive Modeling
Machine Learning Methods
Plotly
Data Presentation
Pandas (Python Package)
Data Science
Exploratory Data Analysis

Shareable Certificate

Earn a shareable certificate to add to your LinkedIn profile

Outcomes

  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 5 modules in this course

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.

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.

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.

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.

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.