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.
Data Science with R - Capstone Project
This course is part of multiple programs.
Instructors: Jeff Grossman
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(80 reviews)
What you'll learn
Write a web scraping program to extract data from an HTML file using HTTP requests and convert the data to a data frame.
Prepare data for modelling by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.
Interpret datawithexploratory data analysis techniques by calculating descriptive statistics, graphing data, and generating correlation statistics.
Build a Shiny app containing a Leaflet map and an interactive dashboard then create a presentation on the project to share with your peers.
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There are 6 modules in this course
What's included
2 videos1 assignment3 app items5 plugins
What's included
1 video1 assignment2 app items3 plugins
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:
What's included
1 video1 assignment3 app items3 plugins
What's included
1 video1 assignment2 app items2 plugins
What's included
1 video1 assignment1 ungraded lab3 plugins
What's included
2 videos3 readings1 peer review5 plugins
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