Simpliv LLC

Data Visualization Principles

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Course Information

Schedules
  • 15 Apr 2025 (Tue) 12:00 AM - 3:00 AM
Registration period
17 Mar 2025 (Mon) - 14 Apr 2025 (Mon)
Price
HKD 1,935
(Live+Recorded Single Attendee
US$249 6 month Access for Rec
Recorded Single Attendee
US$199 6 month Access for Rec
Live Single Attendee
$149 Live Session)
Course Level
Study Mode
Duration
1 Day(s)
Language
English
Location
-
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Course Overview

About the Course
This course offers a deep dive into the principles of data visualization, exploring key concepts such as visual perception, the psychology of color, chart selection, and storytelling with data.

Participants will engage in hands-on exercises to apply these principles, using popular visualization tools to create impactful and insightful data representations. By the end of this course, you'll have a portfolio of visualizations and a solid understanding of how to make data-driven decisions and communicate them effectively.

Course Objective
Understanding the principles of data visualization is crucial for anyone looking to communicate data-driven insights clearly and compellingly. This course will guide you through the process of choosing the right visualization techniques for various types of data, ensuring your visualizations are not only aesthetically appealing but also accurate and informative. Through interactive sessions, you'll learn to avoid common pitfalls and embrace best practices that enhance data comprehension for your audience.

Who is the Target Audience?

  • Data Analysts
  • Business Intelligence Professionals
  • Marketing Analysts
  • Academic Researchers
  • Anyone interested in data science or analytics

Basic Knowledge
No prior knowledge is required

What You’ll Learn

Curriculum

  • Fundamentals of visual perception and the science behind data visualization
  • The psychology of color in data representation
  • Choosing the right chart types for your data
  • Techniques for enhancing clarity and impact in visual storytelling
  • Best practices for designing interactive visualizations
  • Case studies of effective and ineffective data visualizations


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