R Data Science Capstone Project

In this capstone course, you will apply various data science skills and techniques that you have learned as part of the previous courses in the IBM Data Science with R or IBM Data Analytics with Excel and R Professional Certificate Programs.

In this capstone project, you will take on the role of a data scientist who has recently joined an organization and is presented with a challenge that requires data collection, analysis, basic hypothesis testing, visualization, and modeling to be performed on real-world datasets. You will collect and understand data from multiple sources, conduct data wrangling and preparation with Tidyverse, perform exploratory data analysis with SQL, Tidyverse and ggplot2, model data with linear regression, create charts and plots to visualize the data, and build an interactive dashboard.

The project will culminate with a presentation of your data analysis report, with an executive summary for the various stakeholders in the organization.

Course Syllabus

Module 1 - Capstone Overview and Data Collection

Capstone Overview
Data Collection Overview
Hands-on Lab: Complete the Data Collection with Web Scraping Notebook
Hands-on Lab: Complete the Data Collection with OpenWeather API Notebook
Graded Checkpoints

Module 2 - Data Wrangling

Module Introduction and Learning Objectives
Data Wrangling Overview
Hands-on Lab: Complete Data Wrangling with Regular Expressions Notebook
Hands-on Lab: Complete Data wrangling with dplyr Notebook
Graded Checkpoints

Module 3 - Performing Exploratory Data Analysis with SQL, Tidyverse & ggplot2

Module Introduction and Learning Objectives
Hands-on Lab: Load Data into Db2 on IBM Cloud
Hands-on Lab: Complete the EDA with SQL Lab
Hands-on Lab: Complete the EDA with Data Visualization Lab
Graded Checkpoints

Module 4 - Building a Shiny Dashboard

Module Introduction and Learning Objectives
Predict Bike-Sharing Demand Using Regression Models
Hands-on Lab: Complete the Building a Baseline Regression Model Lab
Hands-on Lab: Complete the Improving the Linear Model lab
Graded Checkpoints

Module 5 - Building a R Shiny Dashboard App

Module Introduction and Learning Objectives
Create a R Shiny Dashboard
Hands-on Lab: Build a Bike-Sharing Demand Prediction App with R Shiny and Leaflet
Hands-on Lab: Enhance the Bike-Sharing Demand Prediction App with City Details Plots
Graded Checkpoints

Module 6 - Present Your Data-Driven Insights

Module Introduction and Learning Objectives
Elements Of A Successful Data Findings Report
Structure Of A Report
Best Practices For Presenting Your Findings
(Optional) Hands-on Lab: Getting Started With PowerPoint For The Web
(Optional) Hands-on Lab: Basics of PowerPoint
(Optional) Hands-on Lab: Save your PowerPoint Presentation as PDF
Final Submission Overview and Instructions
Exercise: Preparing Your Presentation (with provided slide template)
Peer Review: Submit your Work and Review your Peers

R Data Science Capstone Project

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