Applied Data Science Capstone

Applied Data Science Capstone

This course is part of multiple programs.

Instructors: Yan Luo

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

Details to know

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Assessments

12 assignments

Taught in English

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This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
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There are 5 modules in this course

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.

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.

What's included

3 videos1 reading4 assignments3 app items1 plugin

3 videosTotal 9 minutes

Project Scenario and Overview3 minutesPreview module
Data Collection Overview4 minutes
Data Wrangling Overview2 minutes

1 readingTotal 3 minutes

Course Introduction3 minutes

4 assignmentsTotal 30 minutes

Graded Quiz: Data Collection API with Webscraping8 minutes
Graded Quiz: Data Wrangling Quiz8 minutes
Check Points: Data Collection API6 minutes
Check Points: Data Wrangling 8 minutes

3 app itemsTotal 180 minutes

Hands-on Lab: Complete the Data Collection API Lab60 minutes
Hands-on Lab: Complete the Data Collection with Web Scraping lab60 minutes
Hands-on Lab: Data Wrangling60 minutes

1 pluginTotal 15 minutes

Getting started with GitHub15 minutes

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.

What's included

1 video4 assignments2 app items

1 videoTotal 2 minutes

Exploratory Data Analysis Overview2 minutesPreview module

4 assignmentsTotal 24 minutes

Exploratory Data Analysis using SQL10 minutes
Exploratory Data Analysis for Data Visualization6 minutes
Check Points: Exploratory Analysis Using SQL 2 minutes
Check Points: Complete the EDA with Visualization6 minutes

2 app itemsTotal 120 minutes

Hands-on Lab: Complete the EDA with SQL60 minutes
EDA with Visualization Lab60 minutes

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.

What's included

1 video2 assignments2 app items

1 videoTotal 1 minute

Interactive Visual Analytics and Dashboards1 minutePreview module

2 assignmentsTotal 40 minutes

Graded Quiz: Interactive Visual Analytics and Dashboard10 minutes
Check Points: Interactive Visual Analytics and Dashboard 30 minutes

2 app itemsTotal 120 minutes

Hands-on Lab: Interactive Visual Analytics with Folium lab60 minutes
Hands-on Lab: Build an Interactive Dashboard with Ploty Dash60 minutes

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.

What's included

1 video2 assignments1 app item

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.