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CS642 | Data Visualization

Track :

Programming

Lessons no : 233

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What will you learn in this course?
  • Create compelling charts, graphs, and maps to communicate complex data insights effectively using visualization tools
  • Apply best practices in data visualization design to enhance clarity, readability, and audience engagement
  • Interpret trends, outliers, and patterns in data through visual analysis for informed decision-making
  • Utilize popular data visualization software such as Tableau, Power BI, or matplotlib for practical projects
  • Design interactive dashboards that enable dynamic data exploration and storytelling
  • Implement data cleaning and preprocessing techniques to prepare datasets for visualization tasks
  • Evaluate the effectiveness of different visualization types for specific data analysis objectives
  • Integrate data visualization into reports and presentations to support data-driven communication strategies
  • Develop custom visualizations to address unique data analysis challenges and requirements
  • Use color theory and visual hierarchy principles to improve the impact of data visualizations
  • Apply statistical concepts to enhance the accuracy and relevance of visual data representations
  • Create geographic visualizations like maps to analyze spatial data and regional trends
  • Optimize visualizations for web and mobile platforms to ensure accessibility and responsiveness
  • Identify and avoid common pitfalls and misleading practices in data visualization
  • Leverage open-source libraries and tools for scalable and customizable data visualization solutions
  • Collaborate with teams to develop comprehensive visual analytics projects for diverse audiences

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Lessons | 233
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Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.