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Jane Wall
In this third and final course of the "Expressway to Data Science: R Programming and Tidyverse" specialization you will reinforce and display your R and tidyverse skills by completing an analysis of COVID-19 data! Here is a chance to apply your skills to a real-world dataset that has effected all of us.
Read more
In this third and final course of the "Expressway to Data Science: R Programming and Tidyverse" specialization you will reinforce and display your R and tidyverse skills by completing an analysis of COVID-19 data! Here is a chance to apply your skills to a real-world dataset that has effected all of us.
Read more
In this third and final course of the "Expressway to Data Science: R Programming and Tidyverse" specialization you will reinforce and display your R and tidyverse skills by completing an analysis of COVID-19 data! Here is a chance to apply your skills to a real-world dataset that has effected all of us.
Throughout the capstone, you will import COVID-19 data; clean, tidy, and join datasets; and develop visualizations. You will also provide some analysis and interpretation to your results, preparing you for your journey into data science. By the end of the course, you will have developed a report that you can add to or use to begin a data science portfolio.
The course logo was created using images of stickers from the RStudio shop. Please visit https://swag.rstudio.com/s/shop.
Register for this course and see more details by visiting:
OpenCourser.com/course/5l64ku/r
What's inside
Syllabus
COVID-19 Data Analysis: Getting Started
This week, you will be introduced to the capstone project, and complete Part 1 of the project. In Part 1, you will import COVID-19 data provided by the New York Times to analyze how COVID-19 impacted the United States through case and death statistics.
Read more
Syllabus
COVID-19 Data Analysis: Getting Started
This week, you will be introduced to the capstone project, and complete Part 1 of the project. In Part 1, you will import COVID-19 data provided by the New York Times to analyze how COVID-19 impacted the United States through case and death statistics.
Read more
COVID-19 Data Analysis: US State Comparison
Last week, you analyzed the number of cases and deaths throughout the United States. This week, you will turn your attention to specific states of your choice to understand how case and deaths rates differed state by state.
COVID-19 Data Analysis: Worldwide Data
COVID-19 was a global pandemic and during this final week you will import global COVID-19 data from Johns Hopkins University to investigate COVID-19 cases and deaths in other countries.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Helps learners get comfortable with cleaning and tidying data before analysis
Prepares learners for work in data science
Covers a real-world dataset
Develops visualization skills
Provides practice with data analysis
Save this course
Save R Programming and Tidyverse Capstone Project to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in R Programming and Tidyverse Capstone Project with these
activities:
Read 'R for Data Science' by Haddock and Ostry
Show steps
Provides a solid foundation in R programming, complementing the course content and reinforcing essential skills.
View
R for Data Science: Import, Tidy, Transform,...
on Amazon
Show steps
-
Read chapters 1-3
-
Complete the exercises in chapters 1-3
Review basic statistics concepts
Show steps
Refreshes fundamental statistics knowledge, ensuring a strong foundation for the course content and data analysis.
Browse courses on
Statistics
Show steps
-
Review mean, median, and standard deviation
-
Review hypothesis testing
Analyze COVID-19 case and death data for a specific US state
Show steps
Provides hands-on practice with data analysis and interpretation, reinforcing understanding of the course concepts.
Browse courses on
Data Analysis
Show steps
-
Choose a US state
-
Import COVID-19 data for the state
-
Analyze the data to identify trends and patterns
-
Write a summary of your findings
Four other activities
Expand to see all activities and additional details
Show all seven activities
Develop a data visualization of COVID-19 cases and deaths in the US
Show steps
Creates a practical application of the skills learned in the course, solidifying understanding of data visualization and analysis techniques.
Browse courses on
Data Visualization
Show steps
-
Import COVID-19 data from the New York Times
-
Clean and tidy the data
-
Create visualizations to display the data
-
Write a summary of your findings
Write a blog post about the impact of COVID-19 on a specific industry
Show steps
Encourages students to apply their knowledge to a real-world scenario, developing their communication and data storytelling skills.
Browse courses on
Data Storytelling
Show steps
-
Choose an industry
-
Research the impact of COVID-19 on the industry
-
Write a blog post that summarizes your findings
-
Share your blog post with others
Contribute to an open-source data science project
Show steps
Encourages students to engage in the open-source community, fostering collaboration and contributing to the advancement of data science.
Browse courses on
Data Science
Show steps
-
Find an open-source data science project
-
Identify a way to contribute
-
Make a contribution to the project
Participate in a data science hackathon
Show steps
Provides a challenging and collaborative environment to apply skills and knowledge, promoting teamwork and innovation.
Browse courses on
Data Science
Show steps
-
Find a data science hackathon
-
Form a team
-
Work on the hackathon project
-
Present your project at the hackathon
Read 'R for Data Science' by Haddock and Ostry
Show steps
Provides a solid foundation in R programming, complementing the course content and reinforcing essential skills.
View
R for Data Science: Import, Tidy, Transform,...
on Amazon
Show steps
Show steps
Show steps
- Read chapters 1-3
- Complete the exercises in chapters 1-3
Review basic statistics concepts
Show steps
Refreshes fundamental statistics knowledge, ensuring a strong foundation for the course content and data analysis.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Review mean, median, and standard deviation
- Review hypothesis testing
Analyze COVID-19 case and death data for a specific US state
Show steps
Provides hands-on practice with data analysis and interpretation, reinforcing understanding of the course concepts.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Choose a US state
- Import COVID-19 data for the state
- Analyze the data to identify trends and patterns
- Write a summary of your findings
Four other activities
Expand to see all activities and additional details
Show all seven activities
Develop a data visualization of COVID-19 cases and deaths in the US
Show steps
Creates a practical application of the skills learned in the course, solidifying understanding of data visualization and analysis techniques.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Import COVID-19 data from the New York Times
- Clean and tidy the data
- Create visualizations to display the data
- Write a summary of your findings
Write a blog post about the impact of COVID-19 on a specific industry
Show steps
Encourages students to apply their knowledge to a real-world scenario, developing their communication and data storytelling skills.
Browse courses on
Data Storytelling
Show steps
Show steps
Show steps
- Choose an industry
- Research the impact of COVID-19 on the industry
- Write a blog post that summarizes your findings
- Share your blog post with others
Contribute to an open-source data science project
Show steps
Encourages students to engage in the open-source community, fostering collaboration and contributing to the advancement of data science.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Find an open-source data science project
- Identify a way to contribute
- Make a contribution to the project
Participate in a data science hackathon
Show steps
Provides a challenging and collaborative environment to apply skills and knowledge, promoting teamwork and innovation.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Find a data science hackathon
- Form a team
- Work on the hackathon project
- Present your project at the hackathon
Career center
Learners who complete R Programming and Tidyverse Capstone Project will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data analysts use data to solve business problems and make informed decisions. They collect, clean, and analyze data, and then develop visualizations and reports to communicate their findings. The R Programming and Tidyverse Capstone Project provides a comprehensive introduction to data analysis and visualization techniques. This course will help you develop the skills needed to work with data, identify trends and patterns, and make recommendations based on data-driven insights.
Biostatistician
Biostatistician
Biostatisticians apply statistical methods to a wide range of biological and health-related data, including data from clinical trials, epidemiological studies, and genetic research. The R Programming and Tidyverse Capstone Project provides a solid foundation in data analysis and visualization techniques that are essential for success in this field. This course will help you develop the skills needed to design and conduct statistical studies, analyze data, and interpret results. You will also gain experience in using R and the tidyverse, which are widely used software tools in biostatistics.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes and spread of diseases. They use data to track and analyze disease outbreaks, and to develop strategies to prevent and control them. The R Programming and Tidyverse Capstone Project provides a foundation in data analysis and visualization techniques that are essential for success in epidemiology. This course will help you develop the skills needed to collect, clean, and analyze data, and to identify and interpret trends and patterns.
Data Scientist
Data Scientist
Data scientists use data to build predictive models and solve complex problems. They work in a variety of industries, including finance, healthcare, and technology. The R Programming and Tidyverse Capstone Project provides a solid foundation in data analysis, modeling, and visualization techniques. This course will help you develop the skills needed to build and evaluate predictive models, and to communicate your findings effectively.
Health Data Analyst
Health Data Analyst
Health data analysts use data to improve the quality and efficiency of healthcare delivery. They work with data from electronic health records, claims data, and other sources to identify trends and patterns, and to develop recommendations for improving patient care. The R Programming and Tidyverse Capstone Project provides a solid foundation in data analysis and visualization techniques that are essential for success in health data analysis. This course will help you develop the skills needed to work with health data, identify trends and patterns, and make recommendations based on data-driven insights.
Statistician
Statistician
Statisticians use data to collect, analyze, interpret, and present information. They work in a variety of fields, including research, government, and industry. The R Programming and Tidyverse Capstone Project provides a solid foundation in data analysis and visualization techniques that are essential for success in statistics. This course will help you develop the skills needed to design and conduct statistical studies, analyze data, and interpret results.
Quantitative Analyst
Quantitative Analyst
Quantitative analysts use data to make investment decisions. They develop and use mathematical and statistical models to analyze financial data and identify investment opportunities. The R Programming and Tidyverse Capstone Project provides a solid foundation in data analysis and modeling techniques that are essential for success in quantitative analysis. This course will help you develop the skills needed to build and evaluate financial models, and to make informed investment decisions.
Market Research Analyst
Market Research Analyst
Market research analysts use data to understand consumer behavior and market trends. They conduct surveys, focus groups, and other research studies to collect data on consumer preferences, attitudes, and behaviors. The R Programming and Tidyverse Capstone Project provides a solid foundation in data analysis and visualization techniques that are essential for success in market research. This course will help you develop the skills needed to design and conduct research studies, analyze data, and interpret results.
Research Scientist
Research Scientist
Research scientists use data to conduct research and develop new knowledge. They work in a variety of fields, including medicine, engineering, and social science. The R Programming and Tidyverse Capstone Project provides a solid foundation in data analysis and visualization techniques that are essential for success in research. This course will help you develop the skills needed to design and conduct research studies, analyze data, and interpret results.
Public Health Analyst
Public Health Analyst
Public health analysts use data to improve the health of populations. They work with data from a variety of sources, including vital records, health surveys, and environmental data, to identify and address public health problems. The R Programming and Tidyverse Capstone Project provides a solid foundation in data analysis and visualization techniques that are essential for success in public health. This course will help you develop the skills needed to work with public health data, identify trends and patterns, and make recommendations for improving the health of populations.
Machine Learning Engineer
Machine Learning Engineer
Machine learning engineers build and maintain machine learning models. They work with a variety of data sources and machine learning algorithms to develop models that can make predictions or decisions. The R Programming and Tidyverse Capstone Project provides a foundation in data analysis and modeling techniques that are essential for success in machine learning engineering. This course will help you develop the skills needed to build and evaluate machine learning models, and to work with large datasets.
Data Engineer
Data Engineer
Data engineers design and build data pipelines that collect, clean, and process data. They work with a variety of data sources, including databases, data warehouses, and cloud storage. The R Programming and Tidyverse Capstone Project provides a foundation in data analysis and visualization techniques that are essential for success in data engineering. This course will help you develop the skills needed to design and build data pipelines, and to work with large datasets.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software applications. They work with a variety of programming languages and software development tools to create software that meets the needs of users. The R Programming and Tidyverse Capstone Project provides a foundation in data analysis and visualization techniques that can be applied to software development. This course will help you develop the skills needed to work with data in software applications, and to develop software that is user-friendly and efficient.
Data Visualization Specialist
Data Visualization Specialist
Data visualization specialists create visual representations of data to communicate information clearly and effectively. They work with a variety of data visualization tools and techniques to create visualizations that are both informative and visually appealing. The R Programming and Tidyverse Capstone Project provides a solid foundation in data analysis and visualization techniques that are essential for success in data visualization. This course will help you develop the skills needed to create clear and effective data visualizations.
Health Educator
Health Educator
Health educators use data to develop and implement health education programs. They work with a variety of populations to promote healthy behaviors and prevent disease. The R Programming and Tidyverse Capstone Project provides a foundation in data analysis and visualization techniques that can be applied to health education. This course will help you develop the skills needed to work with data to identify health needs, develop health education programs, and evaluate the effectiveness of health education programs.
For more career information including salaries, visit:
OpenCourser.com/course/5l64ku/r
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
R Programming and Tidyverse Capstone Project.
Save
Comprehensive introduction to the R programming language. It covers a wide range of topics, from data manipulation to statistical modeling. It valuable resource for anyone who wants to learn how to use R for data science.
Comprehensive introduction to the ggplot2 package, which is used to create elegant graphics for data analysis. It covers a wide range of topics, from basic plots to complex visualizations. It valuable resource for anyone who wants to learn how to use ggplot2 to create beautiful and informative data visualizations.
Comprehensive introduction to statistical inference. It covers a wide range of topics, from the basics of probability to advanced statistical methods. It valuable resource for anyone who wants to learn how to use statistical inference to make informed decisions.
Comprehensive introduction to the TensorFlow library, which is used for deep learning in Python. It covers a wide range of topics, from the basics of TensorFlow to advanced deep learning techniques. It valuable resource for anyone who wants to learn how to use TensorFlow for deep learning.
Comprehensive introduction to the Python programming language. It covers a wide range of topics, from the basics of Python to advanced data analysis techniques. It valuable resource for anyone who wants to learn how to use Python for data analysis.
Comprehensive introduction to the scikit-learn library, which is used for machine learning in Python. It covers a wide range of topics, from the basics of scikit-learn to advanced machine learning techniques. It valuable resource for anyone who wants to learn how to use scikit-learn for machine learning.
Save
Explores the history of epidemics and pandemics, and it argues that we are now on the cusp of a new era in which we can prevent and control these outbreaks. It timely and important read for anyone who wants to understand the challenges and opportunities that the COVID-19 pandemic has presented.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/5l64ku/r
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Effort
3-4 hours per week for 3 weeks
Level
Introductory
Via
Coursera
Institution
University of Colorado Boulder
Instructor
Jane Wall
Language
English
This course belongs to a
collection
called
Expressway to Data Science: R Programming and Tidyverse. It's comprised of three courses:
- Introduction to R Programming and Tidyverse
- Data Analysis with Tidyverse
- R Programming and Tidyverse Capstone Project (viewing)
Good to know
Helps learners get comfortable with cleaning and tidying data before analysis
Prepares learners for work in data science
Covers a real-world dataset
Develops visualization skills
Provides practice with data analysis
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