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Note - SPPU's Degreeplus Beta Version is up, stay tuned for more details.
For Course Creators
For Students
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Data Storytelling & Visualization
Home Skillsoft Data Storytelling & Visualization

Course

Data Storytelling and Visualization

48 hours 40 minutes

Credits: 3 Credits

Description

In this course, learners will develop the skills to communicate data clearly and compellingly through effective visualization and storytelling. Learners will explore data visualization principles, visual design theory, and techniques for identifying and avoiding misleading visuals, applying these concepts through hands-on labs and AI simulator exercises. They will build practical charting skills using Python libraries including Matplotlib and Seaborn, and leverage generative AI and D3.js to create and refine data visualizations. Learners will also work with Google Chart Tools, build and deliver interactive dashboards, and create geographic data stories using Mapbox. They will apply advanced visualization techniques in Python and R, analyze and present data using QlikView, and design professional infographics using Infogram and Visme.

What Students Will Learn

  • Visualizing Data for Impact: Introduction to Data Visualization
  • Introduction to Data Visualization
  • Data Storytelling Lab: Introduction to Data Visualization
  • Visualizing Data for Impact: Analyzing Misleading Visualizations
  • Analyzing Misleading Visualizations
  • Analyzing Misleading Visualizations Lab: Green Lake Auto
  • Visualizing Data for Impact: Data Storytelling
  • Story Telling with Data
  • Data Storytelling
  • Data Storytelling Lab: Green Lake Auto
  • Data Visualization: Best Practices for Creating Visuals
  • Skill Benchmark: Visualizing Data for Impact Literacy (Beginner Level)

  • Visualizing Data for Impact: Visual Design Theory
  • Visual Design Theory
  • Visual Design Theory Lab: Visualize Global Trade
  • Skill Benchmark: Visualizing Data for Impact Competency (Intermediate Level)

  • Make A Line Chart with Matplotlib
  • Make A Line Chart with Matplotlib: Precipitation Lab
  • Make A Bar Chart, Scatterplot, Pie Chart and Histogram with Matplotlib
  • Make A Bar Chart, Scatterplot, Pie Chart and Histogram with Matplotlib Lab: Silly's Ice Cream Shop

  • Making A Visual Argument with Matplotlib
  • Making A Visual Argument with Matplotlib Lab: Compare Grammy Win Records

  • Seaborn Make Charts
  • Seaborn Modify Chart Parameters
  • Make Publishable Charts in Seaborn Lab: Behavioral Risk Factors

  • Build a D3.js Visualization with Generative AI
  • Data Visualization Lab: Visualize the Central Park Squirrel Census with D3.js and Generative AI Part 1
  • Troubleshoot and Refine Generative AI Data Visualization
  • Data Visualization Lab: Visualize the Central Park Squirrel Census with D3.js and Generative AI Part 2
  • AI-Accelerated Data Visualization and Communication

  • Google Chart Tools: Basic Charts
  • Google Chart Tools: Interacting with Charts
  • Google Chart Tools: Advanced Visuals with Charts

  • Delivering Dashboards: Management Patterns
  • Delivering Dashboards: Exploration & Analytics

  • Advanced Visualizations & Dashboards: Visualization Using Python
  • Advanced Visualizations & Dashboards: Visualization Using R
  • Skill Benchmark: Data Visualization Literacy (Beginner Level)

  • Introduction to Data Mapping
  • Introduction to Data Mapping Lab: Solving Spatial Data Problems
  • Create a Map Style in Mapbox Studio
  • Create a Mapbox Style Lab: London Bicycle Share
  • Build a Custom Web Map with Mapbox
  • Build a Custom Web Map with Mapbox Lab: London Bicycle Share

  • QlikView: Getting Started with QlikView for Data Visualization
  • QlikView: Creating Line Charts, Combo Charts, Pivot Tables, & Block Charts
  • QlikView: Creating Mekko Charts, Radar Charts, Gauge Charts, & Scatter Charts
  • Final Exam: Data Visualization with BI Tools
  •  

  • Infogram: Getting Started
  • Infogram: Advanced Features
  • Visme: Introduction
  • Visme: Exploring Charts
  • Visme: Designing a Presentation
  • Final Exam: Creating Infographics for Data Visualizations

  • Create a Map Style in Mapbox Studio Cheatsheet
  • Build a Custom Web Map with Mapbox Cheatsheet

Overall Learning Outcomes

  • Apply data visualization principles to design clear, accurate, and impactful visual representations of data
  • Identify and critically analyze misleading visualizations and apply best practices to avoid them
  • Craft compelling data stories that communicate insights effectively to diverse audiences
  • Build a range of charts including line, bar, scatter, pie, and histogram using Matplotlib and Seaborn in Python
  • Construct and refine data visualizations using D3.js with the assistance of generative AI tools
  • Create interactive and advanced charts using Google Chart Tools
  • Design and deliver dashboards that support management decisions and exploratory analytics
  • Produce advanced visualizations using Python and R
  • Build geographic data stories and custom web maps using Mapbox and data mapping techniques
  • Analyze and present data using QlikView, including advanced chart types such as Mekko, radar, and gauge charts
  • Design professional infographics and presentations using Infogram and Visme
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