1. Introduction to Tableau: Familiarize yourself with the Tableau interface, its various components, and the fundamental concepts of data visualization.

2. Data Connection and Import: Learn how to connect to different data sources, import data into Tableau, and handle common data-related challenges.

3. Data Preparation and Cleansing: Explore techniques for preparing and cleansing data to ensure accuracy and consistency for analysis and visualization.

4. Building Visualizations: Gain hands-on experience in creating a variety of visualizations, including bar charts, line graphs, scatter plots, maps, and more.

5. Advanced Visualization Techniques: Dive into advanced visualization techniques, such as heat maps, treemaps, dual-axis charts, and custom visualizations to present complex data relationships effectively.

6. Calculations and Expressions: Understand the power of calculations and expressions in Tableau to create new fields, perform mathematical operations, and manipulate data.

7. Interactive Dashboards: Learn how to design interactive dashboards that allow users to explore data, filter information, and gain insights at a glance.

8. Storytelling with Data: Discover the art of storytelling through data by creating compelling narratives and engaging visual presentations using Tableau's storytelling features.

9. Data Blending and Joins: Master the art of blending data from multiple sources and performing joins to create a unified and comprehensive dataset for analysis.

10. Data Analytics and Insights: Explore advanced analytical features in Tableau, such as trend lines, forecasting, clustering, and statistical analysis, to uncover meaningful insights from your data.

11. Sharing and Collaboration: Understand different methods for sharing Tableau visualizations with others, publishing to Tableau Server or Tableau Public, and collaborating on projects.

12. Best Practices and Performance Optimization: Learn industry best practices for efficient workbook design, performance optimization, and maintaining data integrity in Tableau.

Course Duration: The course is designed to be completed over a period of 5-6 weeks, with approximately 1 hours of study per day. However, the duration can be adjusted based on your learning pace and schedule.

Prerequisites:

• No prior knowledge of Tableau is required.
• Basic understanding of data analysis concepts is beneficial but not mandatory.

Target Audience:

• Data analysts and data scientists seeking to enhance their data visualization and analysis skills.
• Business professionals who want to effectively communicate data-driven insights and make informed decisions.
• Students and researchers in fields such as data science, business analytics, and information systems.
• Anyone interested in learning Tableau and leveraging its capabilities for data visualization and analysis.