Data Visualization Principles and Data Analysis
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Training TypeLive Training
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CategoryData & Analytics
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Duration2 Hours
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Rating4.9/5
Course Introduction
About the Course
This course introduces participants to the fundamental principles of data visualization alongside core concepts of data analysis. Designed for beginners and intermediate learners, this engaging two-hour course combines theoretical knowledge with practical applications, enabling participants to transform raw data into insightful, compelling visual stories. Through interactive lessons, real-world examples, and hands-on exercises, learners will gain the skills needed to effectively analyze data and use visualization tools to communicate findings clearly and effectively.
Materials and Resources Provided:
Access to data visualization software for practical exercises.
- A selection of datasets for analysis and visualization practice.
- Comprehensive course notes and reference materials.
Course Objective
Upon successful completion of this course, participants will be able to:
Understand Data Visualization Principles:
- LO1.1: Identify the purposes and importance of data visualization in various contexts.
- LO1.2: Recognize the principles of effective visual design for data presentation.
- Master Data Analysis Techniques:
- LO2.1: Perform basic data analysis to extract meaningful information from datasets.
- LO2.2: Utilize statistical methods to summarize data insights.
- Develop Visualization Skills Using Popular Tools:
- LO3.1: Apply data visualization techniques using tools like Tableau, Power BI, or Excel.
- LO3.2: Create various types of charts, graphs, and interactive dashboards.
Who is the Target Audience?
This course is ideal for aspiring data analysts, business professionals, students, and anyone interested in learning how to use data visualization and analysis to make informed decisions and communicate insights.
Basic Knowledge
No prior experience in data analysis or visualization is required, although a basic understanding of Microsoft Excel and a keen interest in data interpretation will be beneficial.
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