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Data Science with R - Capstone Project

IBM via Coursera


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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.


  • Module 1 - Capstone Overview and Data Collection
  • Module 2 - Data Wrangling
  • Module 3: Performing Exploratory Data Analysis with SQL, Tidyverse & ggplot2
    • At this stage of the Capstone Project, you have gained some valuable working knowledge of data collection and data wrangling. You have also learned a lot about SQL querying and visualization. Congratulations! Now it's time to apply some of your new knowledge and learn about Exploratory Data Analysis (EDA) techniques, again through practice. You can use the datasets you wrangled in the previous Module. However, if you had any issues completing the wrangling, no worries - we have prepared some clean datasets for you to use. You will be asked to complete three labs:
  • Module 4: Predictive Analysis
  • Module 5 - Building a R Shiny Dashboard App
  • Module 6 - Present Your Data-Driven Insights

Taught by

Yan Luo


4.6 rating at Coursera based on 69 ratings

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