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Developing Data Products
Roger D. Peng, PhD,
Brian Caffo, PhD,
and
Jeff Leek, PhD
Roger D. Peng, PhD,
Brian Caffo, PhD,
and
Jeff Leek, PhD
A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference. This course covers the basics of creating data products using Shiny, R packages, and interactive graphics. The course will focus on the statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience.
Register for this course and see more details by visiting:
OpenCourser.com/course/2rex6h/developing
What's inside
Syllabus
Course Overview
In this overview module, we'll go over some information and resources to help you get started and succeed in the course.
Shiny, GoogleVis, and Plotly
Read more
Syllabus
Course Overview
In this overview module, we'll go over some information and resources to help you get started and succeed in the course.
Shiny, GoogleVis, and Plotly
Read more
Now we can turn to the first substantive lessons. In this module, you'll learn how to develop basic applications and interactive graphics in shiny, compose interactive HTML graphics with GoogleVis, and prepare data visualizations with Plotly.
R Markdown and Leaflet
During this module, we'll learn how to create R Markdown files and embed R code in an Rmd. We'll also explore Leaflet and use it to create interactive annotated maps.
R Packages
In this module, we'll dive into the world of creating R packages and practice developing an R Markdown presentation that includes a data visualization built using Plotly.
Swirl and Course Project
Week 4 is all about the Course Project, producing a Shiny Application and reproducible pitch.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches how to create interactive visualizations and web-based data products, which is a common skill to have in the data science industry
Instructors are highly recognized for their work in the topic the course teaches
Builds upon learners' existing statistical knowledge and strengthens their statistical foundation in the context of data products
Uses a mix of media and materials, including videos, readings, discussions, hands-on labs, and interactive materials
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Save Developing Data Products to your list so you can find it easily later:
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Reviews summary
Data product development course
According to students, "Developing Data Products" is well-received and engaging. Learners found it especially useful for gaining practical experience in developing data products using R and Shiny. The course project is a highlight for many, allowing them to apply learned skills to create their own data products.
The course provides a good overview of Shiny.
"Good overview of tools to use in rstudio to produce data products."
"Especially liked shiny: efficient tool to produce useful data products on the web."
Students enjoyed the final project.
"This is the 9th course in the series I completed and I found it the most fun."
"I also learned a tremendous amount that I have directly applied at work."
"The course project is much more flexible than the prior course projects and allows a student to develop a data product of their own choosing."
One student had a negative experience.
"The title should be more like "Developing Money From Gullible Students Who Don't Know Any Better"."
"Don't take this course, you will not bring anything out of it."
Career center
Learners who complete Developing Data Products will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists are responsible for developing and implementing data-driven solutions to business problems. They use their skills in statistics, machine learning, and data mining to help businesses make better decisions. This course can help you develop the skills you need to be a successful Data Scientist. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Statistician
Statistician
Statisticians are responsible for collecting, analyzing, and interpreting data. They use their findings to help businesses make better decisions. This course can help you develop the skills you need to be a successful Statistician. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data. They use their findings to help businesses make better decisions. This course can help you develop the skills you need to be a successful Data Analyst. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Financial Analyst
Financial Analyst
Financial Analysts are responsible for analyzing financial data to make investment recommendations. They use their skills in statistics, finance, and economics to help investors make better decisions. This course can help you develop the skills you need to be a successful Financial Analyst. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Business Analyst
Business Analyst
Business Analysts are responsible for analyzing business problems and recommending solutions. They use their skills in data analysis, process improvement, and problem-solving to help businesses improve their performance. This course can help you develop the skills you need to be a successful Business Analyst. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts are responsible for developing and implementing mathematical models to optimize business operations. They use their skills in statistics, optimization, and simulation to help businesses improve their efficiency and effectiveness. This course can help you develop the skills you need to be a successful Operations Research Analyst. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Market Researcher
Market Researcher
Market Researchers are responsible for conducting research to understand consumer behavior. They use their findings to help businesses develop new products and services. This course can help you develop the skills you need to be a successful Market Researcher. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. They use their skills in machine learning, computer science, and mathematics to create machine learning models that can solve complex problems. This course can help you develop the skills you need to be a successful Machine Learning Engineer. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products. They use their skills in product management, marketing, and business strategy to create products that meet the needs of users. This course can help you develop the skills you need to be a successful Product Manager. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Data Engineer
Data Engineer
Data Engineers are responsible for designing, building, and maintaining data pipelines. They use their skills in data engineering, software engineering, and computer science to create data pipelines that can process and analyze large amounts of data. This course can help you develop the skills you need to be a successful Data Engineer. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists are responsible for creating visual representations of data. They use their skills in data visualization, graphic design, and storytelling to create data visualizations that can communicate complex information in a clear and concise way. This course can help you develop the skills you need to be a successful Data Visualization Specialist. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts are responsible for using mathematical and statistical models to analyze financial data. They use their skills in mathematics, statistics, and finance to create models that can predict the performance of financial instruments. This course can help you develop the skills you need to be a successful Quantitative Analyst. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
UX Designer
UX Designer
UX Designers are responsible for designing the user experience of digital products. They use their skills in user experience design, human-computer interaction, and psychology to create digital products that are easy to use and enjoyable to interact with. This course can help you develop the skills you need to be a successful UX Designer. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Data Journalist
Data Journalist
Data Journalists are responsible for using data to tell stories. They use their skills in journalism, data analysis, and data visualization to create data-driven stories that can inform and educate the public. This course can help you develop the skills you need to be a successful Data Journalist. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. They use their skills in computer science, software engineering, and mathematics to create software that meets the needs of users. This course can help you develop the skills you need to be a successful Software Engineer. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.
For more career information including salaries, visit:
OpenCourser.com/course/2rex6h/developing
Reading list
We've selected 25 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
Developing Data Products.
Classic textbook on statistical learning methods. It may be useful for students who want to learn more about the theory and practice of statistical learning.
Provides a comprehensive overview of the R programming language and its capabilities for creating interactive data visualizations. It covers the basics of ggplot2 and plotly, and how to use them to create a variety of visualizations, including charts, maps, and dashboards.
Provides a comprehensive guide to ggplot2, a powerful data visualization library for R. It covers the basics of ggplot2, as well as advanced topics such as creating complex visualizations and using ggplot2 to create reports.
Comprehensive guide to reinforcement learning methods and techniques. It may be useful for students who want to learn more about how to build and evaluate reinforcement learning models.
Save
Provides a comprehensive guide to R Markdown, a powerful tool for creating dynamic, reproducible reports and documents. It covers the basics of R Markdown, as well as advanced topics such as creating interactive documents and using R Markdown to create presentations.
Provides a broad overview of the data science process, including data collection, cleaning, analysis, and visualization. It may be useful for students who want to learn more about the big picture of data science.
Provides a comprehensive overview of statistical methods for data analysis. It may be useful for students who want to learn more about the theory and practice of statistical analysis.
Provides a comprehensive overview of regression and multilevel/hierarchical models. It may be useful for students who want to learn more about these topics.
Save
Provides a comprehensive overview of causal inference methods. It may be useful for students who want to learn more about how to design and analyze causal studies.
Save
Comprehensive guide to deep learning methods and techniques. It may be useful for students who want to learn more about how to build and evaluate deep learning models.
Provides a comprehensive guide to deep learning, using R. It covers the basics of deep learning, as well as advanced topics such as convolutional neural networks and recurrent neural networks.
Save
Provides a comprehensive guide to natural language processing, using R. It covers the basics of natural language processing, as well as advanced topics such as text mining and machine learning.
Provides a comprehensive guide to R programming for data science. It covers a wide range of topics, from the basics of R to advanced techniques for data analysis and visualization.
Provides a comprehensive introduction to machine learning, using R. It covers the basics of machine learning, as well as advanced topics such as supervised and unsupervised learning.
Provides a comprehensive introduction to statistical learning, covering the basics of supervised and unsupervised learning.
Save
Provides a comprehensive guide to predictive modeling, using R. It covers the basics of predictive modeling, as well as advanced topics such as feature selection and model evaluation.
Provides a comprehensive introduction to data science, covering the basics of data science, as well as advanced topics such as data mining and machine learning.
This comprehensive classic textbook covers a broad range of statistical methods, some of which may be useful background material for some students in this course.
Save
Is an excellent introduction to the R programming language, and provides a comprehensive overview of its features and capabilities.
Save
Provides a practical introduction to data visualization, covering the basics of visual perception and how to use different types of visualizations to communicate data effectively.
Provides a comprehensive introduction to Bayesian statistics, using R and Stan. It covers the basics of Bayesian statistics, as well as advanced topics such as hierarchical models and Markov chain Monte Carlo.
Save
Provides a comprehensive guide to R programming for data science. It covers a wide range of topics, from the basics of R to advanced techniques for data analysis and visualization.
May be useful for students who are new to R, as it provides a gentle introduction to the language and some of its statistical capabilities.
Save
Provides a comprehensive guide to time series analysis with R. It covers a wide range of topics, from the basics of time series analysis to advanced techniques for forecasting and modeling time series data.
Save
Provides a comprehensive guide to advanced R programming. It covers a wide range of topics, from the basics of R programming to advanced techniques for data analysis and visualization.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/2rex6h/developing
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Via
Coursera
Institution
Johns Hopkins University
Instructors
Roger D. Peng, PhD
Brian Caffo, PhD
Jeff Leek, PhD
Language
English
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آذربایجان دیلی
This course belongs to a
collection
called
Data Science. It's comprised of 11 courses:
Good to know
Teaches how to create interactive visualizations and web-based data products, which is a common skill to have in the data science industry
Instructors are highly recognized for their work in the topic the course teaches
Builds upon learners' existing statistical knowledge and strengthens their statistical foundation in the context of data products
Uses a mix of media and materials, including videos, readings, discussions, hands-on labs, and interactive materials
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