Advanced Data Applications and Integration
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May 2026
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There are 6 modules in this course
Take your R programming skills to the next level with this final, practical course that bridges theory and real-world applications. Learn to collect data from web sources, create interactive visualizations, handle large datasets efficiently, and integrate with cloud services. While covering advanced topics, the course maintains a beginner-friendly approach with step-by-step guidance and AI assistance.
By the end of this course, you will be able to: Collect and process data from web sources using scraping and API techniques, transforming raw online data into structured, analysis-ready formats. Build interactive visualizations and dashboards that allow audiences to explore data dynamically, going beyond static charts and reports. Integrate R workflows with cloud services and external platforms, enabling you to build end-to-end data pipelines that connect collection, analysis, and delivery.
In this module, you’ll use one of the most valuable data skills out there: collecting real-time information from the web. You’ll learn how to use tools like rvest and APIs to extract data from websites and online platforms. You’ll learn how to use tools like rvest and APIs to extract data from websites and online services in ways that are practical, efficient, and aligned with ethical standards. You’ll practice turning live websites into structured datasets and set up workflows that save you time and effort. Whether you’re tracking trends, pulling social media data, or automating updates, these skills give you a serious edge.
What's included
6 videos7 readings2 assignments2 ungraded labs
6 videos•Total 20 minutes
- Introduction to Advanced Data Applications and Integration•3 minutes
- Introduction to Web Scraping Use Cases & Ethics•3 minutes
- Hands-on with rvest: A Practical Guide•3 minutes
- AI-Assisted Web Scraping Code Generation•4 minutes
- Making basic API calls•3 minutes
- Using AI tools for API code generation •3 minutes
7 readings•Total 56 minutes
- Course Syllabus•3 minutes
- Using R in your Visual Studio Code Lab •5 minutes
- Connecting Copilot in your Visual Studio Code Labs•10 minutes
- Introduction to Web Data Collection •7 minutes
- Web Scraping Fundamentals•8 minutes
- Understanding APIs: Your Gateway to Data•8 minutes
- API Fundamentals and Implementation•15 minutes
2 assignments•Total 40 minutes
- Web Scraping Concepts Assessment•20 minutes
- API Fundamentals Assessment•20 minutes
2 ungraded labs•Total 120 minutes
- Basic Web Scraping Practice•60 minutes
- First Steps with APIs•60 minutes
In this module, you’ll build a strong foundation in working with geographic data, an essential skill for mapping patterns, trends, and relationships that numbers alone can’t show. Using the leaflet package, you’ll create interactive maps that go beyond static visuals. You’ll learn how to add markers, layers, and controls that let users explore your data in meaningful ways. Whether you're analyzing locations, tracking movement, or sharing insights with non-technical stakeholders, spatial visualizations can bring your work to life, and this module shows you how to start.
What's included
6 videos4 readings3 assignments2 ungraded labs
6 videos•Total 18 minutes
- Why Maps Matter: Real-World Applications •3 minutes
- Looking at different types of maps•4 minutes
- Building Your First Interactive Map•3 minutes
- Essential Interactive Features in leaflet•2 minutes
- Advanced Leaflet Features•3 minutes
- Interactive Visualization Best Practices•3 minutes
4 readings•Total 27 minutes
- Introduction to Geographic Data•7 minutes
- Geographic Data Fundamentals•6 minutes
- Leaflet Fundamentals and Interactivity•8 minutes
- Advanced Interactive Mapping•6 minutes
3 assignments•Total 65 minutes
- Geographic Data Concepts Assessment•20 minutes
- Interactive Mapping Concepts•20 minutes
- Advanced Interactive Features Assessment•25 minutes
2 ungraded labs•Total 120 minutes
- Building Interactive Maps•60 minutes
- Advanced Interactive Mapping•60 minutes
In this module, you’ll learn how to handle large datasets with speed and precision using the data.table package, one of R’s most powerful tools for high-performance data manipulation. You’ll explore techniques that make your code faster and more scalable, especially for complex tasks that push beyond what traditional tools can handle. Through real-world examples and focused practice, you’ll see why data.table is a go-to choice for working data professionals. If you’re dealing with big data, or want to write code that feels sharp and efficient, this module will show you how.
What's included
3 videos3 readings2 assignments
3 videos•Total 11 minutes
- Why data.table? Real-World Applications•3 minutes
- Getting Started with data.table•4 minutes
- Optimizing data.table Operations•5 minutes
3 readings•Total 15 minutes
- data.table Fundamentals•5 minutes
- data.table Syntax Guide•4 minutes
- Advanced data.table Concepts•6 minutes
2 assignments•Total 40 minutes
- data.table Basics Assessment•20 minutes
- Advanced data.table Operations Assessment•20 minutes
In this module, you’ll take your reporting skills to the next level with advanced features in RMarkdown. You’ll learn how to build dynamic, parameter-driven reports that update automatically as your data changes, saving time and reducing manual effort. From filtering content to customizing outputs, you’ll discover how to create reports that are flexible, reusable, and ready for real-world workflows. If you work with stakeholders, share results, or just want to streamline your reporting process, this module gives you the tools to do it smarter.
What's included
3 videos4 readings2 assignments2 ungraded labs
3 videos•Total 14 minutes
- Dynamic Reports in Action•3 minutes
- Creating Dynamic Reports•6 minutes
- Adding Interactive Elements•5 minutes
4 readings•Total 29 minutes
- Dynamic RMarkdown Fundamentals•6 minutes
- Dynamic Text and Conditional Section in RMarkdown•7 minutes
- Making Reports Interactive•8 minutes
- Interactive RMarkdown Features•8 minutes
2 assignments•Total 45 minutes
- Dynamic Reports Assessment•20 minutes
- Interactive Elements Assessment•25 minutes
2 ungraded labs•Total 120 minutes
- Building Dynamic Reports•60 minutes
- Interactive Report Features•60 minutes
In this module, you’ll learn how to work with cloud storage, an essential part of modern data workflows. Using Azure Blob Storage, you’ll practice storing, accessing, and managing data in the cloud. Along the way, you’ll see how cloud-based tools fit into real-world analysis, reporting, and collaboration. Whether you're preparing for larger-scale projects or just want to keep your data work more organized and accessible, this module helps you build the skills to do it with confidence.
What's included
2 videos3 readings1 assignment
2 videos•Total 7 minutes
- Working with Azure Storage Interface•4 minutes
- Managing Files in Azure Blob Storage•4 minutes
3 readings•Total 18 minutes
- Cloud Storage Fundamentals•6 minutes
- Cloud Storage in Data Analysis•10 minutes
- Staying Secure and Cost-Efficient with Azure Blob Storage•2 minutes
1 assignment•Total 25 minutes
- Cloud Storage Concepts Assessment•25 minutes
In this capstone project, you’ll take on a real-world data challenge that brings together everything you've learned: web scraping, data manipulation, interactive visualizations, and dynamic reporting. You’ll also create a polished, professional GitHub portfolio to showcase your work. Capstones can feel like a lot, and that’s completely normal. You’ll have support along the way, and by the end, you’ll walk away with something you can be proud of, and share with confidence.
What's included
4 videos4 readings4 assignments3 ungraded labs
4 videos•Total 10 minutes
- Project Setup and Initial Analysis Steps•3 minutes
- Spatial Visualization Techniques•2 minutes
- Results Presentation•2 minutes
- Organizing Your Portfolio•3 minutes
4 readings•Total 65 minutes
- Study Guide: Preparing Data for Analysis (Optional)•20 minutes
- Study Guide: Modeling and Spatial Analysis (Optional)•20 minutes
- Study Guide: Documentation and Organization (Optional)•20 minutes
- Showcasing Your Data Science Skills•5 minutes
4 assignments•Total 95 minutes
- Project Setup and Initial Analysis Assessment•30 minutes
- Statistical Modeling and Spatial Analysis Assessment•25 minutes
- Documentation and Results Assessment •15 minutes
- Showcasing Your Work: GitHub Portfolio•25 minutes
3 ungraded labs•Total 180 minutes
- Initial Analysis of Taxi Zones•60 minutes
- Statistical Modeling and Spatial Analysis•60 minutes
- Documentation and Results•60 minutes
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