Developing Data Products Course

Developing Data Products Course Course

This course is perfect for learners looking to bridge the gap between data analysis and end-user engagement by building real-world, interactive tools.

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9.7/10 Highly Recommended

Developing Data Products Course on Coursera — This course is perfect for learners looking to bridge the gap between data analysis and end-user engagement by building real-world, interactive tools.

Pros

  • Hands-on Shiny and visualization experience
  • Real-world applications with final capstone
  • Clear explanations and structured workflow
  • Boosts portfolio with a tangible data product

Cons

  • Requires prior knowledge of R
  • Some tools may have a learning curve for beginners

Developing Data Products Course Course

What will you in the Developing Data Products Course

  • Learn how to build and deploy interactive data products.

  • Develop web-based applications using Shiny in R.

  • Create interactive visualizations with GoogleVis, Plotly, and Leaflet.

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  • Use R Markdown to generate dynamic reports.

  • Design and publish custom R packages.

Program Overview

1. Course Overview
Duration: ~1 hour

  • Introduction to data products and course objectives.

  • Overview of tools and software to be used.

2. Interactive Visualizations with Shiny and Plotly
Duration: ~2 hours

  • Build user interfaces and server logic using Shiny.

  • Create dynamic, interactive graphics with Plotly and GoogleVis.

3. Enhancing Data Products with R Markdown and Leaflet
Duration: ~2 hours

  • Generate interactive reports using R Markdown.

  • Build maps and location-based visualizations using Leaflet.

4. Building and Documenting R Packages
Duration: ~2 hours

  • Learn the structure of an R package.

  • Create and document your own package for public or private use.

5. Final Course Project
Duration: ~2 hours

  • Design and submit an original data product.

  • Review and evaluate peer submissions.

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Job Outlook

  • Data Scientists: Showcase results through interactive dashboards and tools.

  • Data Analysts: Build engaging, presentation-ready products for stakeholders.

  • R Developers: Learn how to package and share tools and apps efficiently.

  • Business Professionals: Improve storytelling and decision-making with dynamic data tools.

  • Researchers: Present academic findings in an interactive format.

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