Introduction to Data Visualization - The role of data visualization in data analysis and communication, Types of data visualizations (e.g., charts, graphs, maps), Data visualization tools and software, Overview of popular data visualization tools and software (e.g., Tableau, Excel, Python libraries), Features and capabilities of selected tools, Exploration of design principles, including colour theory, typography, and layout, Importance of visual hierarchy and consistency in visualization design.

Data Visualization Principles - Design principles for effective data visualization, Color theory and usage in data visualization, Human perception and cognition in visualization design, Tools and Techniques, Introduction to data visualization tools (e.g., Tableau, Python libraries)., Creating basic charts and graphs, Interactive and dynamic visualizations

Exploratory Data Visualization - Data exploration and visual data profiling, Univariate and multivariate data visualization, Visualizing patterns, outliers, and distributions, Storytelling with Data, Narrative structure in data storytelling, building data-driven narratives, using visualizations to support storytelling.

Advanced Topics: Geographic and spatial data visualization (e.g., maps and geospatial analysis), Network and hierarchical data visualization, Visualizing time series and temporal data, Future Trends and Emerging Technologies, Exploration of future trends in data visualization, Discussion of emerging technologies (e.g., VR, AR) in data visualization.

Designing reports with visual analytics- Reports of Ratios, Rates Percentage, Mean, Dispersion, Variation over time Maps- Viewing Visual Analytical Reports: Viewing Reports on the Web, Viewing reports on the Mobile Device-Creating analyses and reports with Visual Analytics.