This course is part of Expressway to Data Science: R Programming and Tidyverse.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Expressway to Data Science: R Programming and Tidyverse Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
Instructors:
English
What you'll learn
Import and clean COVID-19 datasets using R and Tidyverse
Create data visualizations to analyze COVID-19 trends
Perform comparative analysis of COVID-19 impact across states
Develop comprehensive data analysis reports
Build a professional data science portfolio piece
Skills you'll gain
This course includes:
0.7 Hours PreRecorded video
3 peer reviews
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
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There are 3 modules in this course
This capstone project focuses on applying R programming and Tidyverse skills to analyze COVID-19 data. Students work with real-world datasets from the New York Times and Johns Hopkins University to perform comprehensive analysis of COVID-19 cases and deaths. The course involves importing, cleaning, and joining datasets, creating visualizations, and developing interpretative reports. Through hands-on practice, students develop a complete data analysis portfolio piece while examining both US and global COVID-19 trends.
COVID-19 Data Analysis: Getting Started
Module 1 · 3 Hours to complete
COVID-19 Data Analysis: US State Comparison
Module 2 · 3 Hours to complete
COVID-19 Data Analysis: Worldwide Data
Module 3 · 3 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Expressway to Data Science: R Programming and Tidyverse
Instructor
Faculty Director of Data Science Programs
Dr. Jane Wall is the Faculty Director of the Data Science Graduate Program at the University of Colorado Boulder, a position she has held since 2021. With a unique blend of business acumen and technical expertise, she brings a diverse background to her role. Dr. Wall began her academic journey with undergraduate degrees in Classical Languages and Political Science, followed by two master’s degrees in Mathematics and Applied Mathematics from the University of Georgia. Her professional experience includes significant roles at IBM, where she worked as a software engineer and manager, as well as leadership positions in various software development companies.Dr. Wall returned to academia to earn her Ph.D. in Computational and Applied Mathematics from Rice University, focusing on computational neuroscience. She has developed and taught numerous data science courses, including "Statistical Programming in R" and "Data Science Practicum." At CU Boulder, she oversees both residential and online modes of the Data Science program, which includes innovative courses like "Algebra and Differential Calculus for Data Science" and "Introduction to R Programming and Tidyverse." Dr. Wall's commitment to advancing data science education is evident through her efforts to create robust curricula that prepare students for successful careers in this rapidly evolving field.
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Frequently asked questions
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