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Duration 35 hours
Course Outline
Introduction
- Introduction to Tableau
- Core concepts of Python, R, and SQL
Getting Started
- Configuring the development environment
- Understanding software integration
Data Analysis with Python
- Python basics and programming syntax
- Loading libraries and datasets
- Data cleaning and transformation
- Data normalization and formatting
- Exploratory data analysis
- Running regression analyses
- Building and assessing models
- Data visualization
Data Analysis with R
- R fundamentals and programming
- Data preparation
- Data classification and handling in R
- Utilizing functions
- Data visualization
Data Analysis with SQL
- Database setup
- Integrating Python with SQL
- Integrating R with SQL
- SQL aggregations and joins
- Database querying
- Data manipulation
Data Visualization Using Tableau
- Tableau design principles for visualization
- Building dashboards, charts, and tables
- Mapping techniques
- Regressions in R and Tableau
- Advanced analytics with R and Tableau
- Real-world examples and use cases
Troubleshooting
Summary and Future Directions
Requirements
- Practical experience with data analysis (e.g., in Excel).
- Basic understanding of database concepts.
- No prior programming experience is necessary.
Target Audience
- Data analysts.
Testimonials (3)
Learning that the QGIS and a tool that can used by other different professionals such land survey
Bame Duncan Koko - Bentel Technologies (Pty) Ltd
Course - QGIS for Geographic Information System
How to use open satellites data for real applications
Tshering Dorji - Druk Holding and Investments
Course - Advanced Geographic Information Systems (GIS)
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
