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Course Outline
Introduction
- Overview of Tableau.
- Core concepts of Python, R, and SQL.
Getting Started
- Configuring the development environment.
- Understanding software integration.
Data Analysis with Python
- Python programming basics.
- Importing libraries and datasets.
- Data wrangling techniques.
- Data normalization and formatting.
- Exploratory data analysis.
- Conducting regression analysis.
- Building and evaluating models.
- Data visualization.
Data Analysis with R
- R programming fundamentals.
- Data preparation.
- Data classification and manipulation in R.
- Utilizing functions.
- Data visualization.
Data Analysis with SQL
- Database setup.
- Connecting Python to SQL.
- Connecting R to SQL.
- SQL aggregations and joins.
- Database querying.
- Data manipulation.
Data Visualization Using Tableau
- Tableau design principles.
- 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 Next Steps
Requirements
- Practical experience with data analysis tools (e.g., Excel).
- A foundational grasp of database concepts.
- No prior programming experience is necessary.
Target Audience
- Data analysts.
35 Hours
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.
