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Data Science with R - Capstone Project
  • Level Professional
  • Duration 26 hours
  • Course by IBM
  • Offered by

About

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 Specialization or IBM Data Analytics with Excel and R Professional Certificate. For this project, you will assume the role of a Data Scientist who has recently joined an organization and be 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.

Modules

Capstone Introduction and Understanding the Datasets

    • 1 Videos
    • 1 ExternalTool
    • 2 Plugin
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1 External Tool

  • (Optional) Obtain an IBM Cloud Feature Code

1 Videos

  • Introduction to Data Science with R Capstone Project

Collecting the Data

    • 1 Videos
    • 2 ExternalTool
    • 3 Plugin
    • 1 Assignment
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1 Assignment

  • Checkpoints

2 External Tool

  • Hands-on Lab: Complete the Data Collection with Web Scraping Notebook
  • Hands-on Lab: Complete the Data Collection with OpenWeather API Notebook

1 Videos

  • Weather and Bike-Sharing Demand Data Collection

Data Wrangling

    • 1 Videos
    • 2 ExternalTool
    • 3 Plugin
    • 1 Assignment
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1 Assignment

  • Checkpoints

2 External Tool

  • Hands-on Lab: Complete Data Wrangling with Regular Expressions Notebook
  • Hands-on lab: Complete Data wrangling with dplyr Notebook

1 Videos

  • Data Wrangling

Performing Exploratory Data Analysis with SQL, Tidyverse & ggplot2

    • 1 Videos
    • 3 ExternalTool
    • 3 Plugin
    • 1 Assignment
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1 Assignment

  • Checkpoints

3 External Tool

  • Hands-on Lab: Complete the EDA with SQL lab using RSQLite
  • (Optional) Hands-on Lab: Complete the EDA with SQL lab using RODBC with IBM DB2
  • Hands-on Lab: Complete the EDA with Data Visualization Lab

1 Videos

  • Exploratory Data Analysis

Predictive Analysis

    • 1 Videos
    • 2 ExternalTool
    • 2 Plugin
    • 1 Assignment
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1 Assignment

  • Checkpoints

2 External Tool

  • Hands-on Lab: Complete the Building a Baseline Regression Model Lab
  • Hands-on Lab: Complete the Improving the Linear Model lab

1 Videos

  • Regression Models

Building a R Shiny Dashboard App

    • 1 Videos
    • 3 Plugin
    • 1 Lab
    • 1 Assignment
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1 Assignment

  • Checkpoints

1 Labs

  • Hands-on Lab: Build a bike-sharing demand prediction app (using Coursera Labs)

1 Videos

  • Building a Dashboard with R Shiny

How to Present Your Findings

    • 2 Videos
    • 4 Plugin
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2 Videos

  • Elements Of A Successful Data Findings Report
  • Best Practices For Presenting Your Findings

Final Presentation

    • 1 Readings
    • 1 PeerReview
    • 1 Plugin
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1 Peer Review

  • Peer Review: Submit your Work and Review your Peers

1 Readings

  • Final Submission Overview and Instructions

Course Wrap-Up

    • 1 Readings
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1 Readings

  • Congratulations and Next Steps

Credits and Acknowledgments

    • 1 Readings
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1 Readings

  • Credits and Acknowledgments

Auto Summary

Enhance your data science skills with the Data Science with R - Capstone Project by Coursera. Tackle real-world challenges as a newly joined Data Scientist, mastering data collection, analysis, hypothesis testing, visualization, and modeling using tools like Tidyverse, SQL, and ggplot2. Conclude with a compelling data analysis report. Ideal for professionals, this comprehensive course is part of the IBM Data Science Specialization and offers flexible subscription options.

Jeff Grossman
Instructors

Jeff Grossman

Yan Luo
Instructors

Yan Luo