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Duration 35 hours
Course Outline
Introduction
- Tableau overview
- Basics of Python, R, and SQL
Initial Setup
- Configuring the development environment
- Grasping software integration
Analyzing Data with Python
- Python core concepts and coding
- Loading libraries and datasets
- Data wrangling
- Normalizing and formatting data
- Exploratory data analysis
- Regression analysis execution
- Building and assessing models
- Data Visualization
Analyzing Data with R
- R core concepts and coding
- Data preparation
- Data classification and manipulation in R
- Function utilization
- Data Visualization
Analyzing Data with SQL
- Database setup
- Linking Python to SQL
- Linking R to SQL
- SQL aggregation and joins
- Database querying
- Data manipulation
Visualizing Data in Tableau
- Tableau design principles for visualization
- Building dashboards, charts, and tables
- Mapping methods
- Regressions in R and Tableau
- Advanced analytics with R and Tableau
- Real-world examples and use cases
Debugging
Recap and Future Steps
Requirements
- Practical experience with data analysis (e.g., via Excel)
- A basic grasp 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.
