What You Need to Know Before
You Start
Starts 7 June 2025 03:17
Ends 7 June 2025
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10 hours 2 minutes
Optional upgrade avallable
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Progress at your own speed
Paid Course
Optional upgrade avallable
Overview
Do you want to enhance your skills and learn everything required to pass both the Desktop Specialist and Data Analyst exam?
Syllabus
- Introduction to Tableau
- Connecting to Data
- Preparing Data
- Creating Visualizations
- Analyzing Data
- Enhancing Analysis
- Sharing and Collaborating
- Exam Preparation: Tableau Desktop Specialist
- Practical Case Studies
- Introduction to Data Analysis
- Preparing for Data Analyst Certification
- Course Conclusion
- Final Assessment
Overview of Tableau Desktop
Key functionalities and user interface
Installing Tableau and setup instructions
Understanding data sources and establishing connections
Working with different file types and databases
Data extraction and live connections
Data cleaning and transformation techniques
Using data interpreter and pivoting data
Creating data extracts and filters
Building basic charts: bar charts, line graphs, scatter plots
Advanced visualizations: maps, dual-axis charts, and histograms
Creating dashboards and stories
Applying filters and sets
Using calculated fields and table calculations
Trend lines, forecasting, and clustering
Using parameters and calculated fields for dynamic analysis
Advanced analytics features: LOD expressions
Understanding reference lines, bands, and distribution models
Publishing data to Tableau Server or Tableau Online
Exporting to PDF, PowerPoint, and image formats
Sharing visualizations on Tableau Public
Overview of the exam format and topics
Practice questions and review sessions
Test-taking strategies and tips
Hands-on exercises with real-world data
End-to-end project: from data connection to dashboard creation
Key concepts in data analysis and statistics
Exploratory data analysis techniques
Overview of the exam and skill requirements
In-depth analysis practice tasks
Mock exams and revision sessions
Review of key concepts and skills
Next steps in further learning and certification paths
Resources for continuous learning and support
Comprehensive project or exam encompassing course material
Taught by
Nikolai Schuler and Ben Butters
Subjects
Data Science