Global Certificate Visual Data R: Design for Insights

• Unit 1: Introduction to Visual Data R: Overview of Visual Data R, understanding data visualization, and its importance in data analysis. • Unit 2: Data Preparation for Visualization: Data cleaning, preprocessing, and manipulation using R. • Unit 3: Data Visualization Tools in R: Exploring popular R packages for data visualization, such as ggplot2, lattice, and plotly. • Unit 4: Chart Design Principles: Best practices for designing effective visualizations, including color theory, typography, and layout. • Unit 5: Creating Statistical Visualizations: Building visualizations for statistical data analysis, including scatter plots, line charts, and bar graphs. • Unit 6: Creating Multivariate Visualizations: Building visualizations for multivariate data analysis, including scatterplot matrices, parallel coordinate plots, and heatmaps. • Unit 7: Advanced Visualization Techniques: Exploring advanced visualization techniques, such as interactive visualizations, network visualizations, and geospatial visualizations. • Unit 8: Visualization Ethics and Bias: Understanding ethical considerations in data visualization, including bias, transparency, and reproducibility. • Unit 9: Communicating Data Insights: Best practices for communicating data insights through visualizations to stakeholders and audiences. • Unit 10: Visual Data R Capstone Project: Applying knowledge and skills gained throughout the course to a real-world data visualization project.