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Course Outline
Introduction
- Overview of Tableau
- Fundamentals of Python, R, and SQL
Getting Started
- Setting up the development environment
- Understanding software integration
Data Analysis with Python
- Python fundamentals and programming
- Importing libraries and datasets
- Wrangling data
- Data normalization and formatting
- Exploratory data analysis
- Performing regression analysis
- Model development and evaluation
- Visualizing Data
Data Analysis with R
- R fundamentals and programming
- Preparing data
- Classifying and working with data in R
- Using functions
- Visualizing Data
Data Analysis with SQL
- Setting up the database
- Connecting Python and SQL
- Connecting R and SQL
- SQL aggregations and joins
- Querying the database
- Manipulating data
Data Visualization Using Tableau
- Tableau design principles for visualization
- Creating dashboards, charts, and tables
- Mapping techniques
- Regressions in R and Tableau
- Advanced analytics with R and Tableau
- Practical examples and use cases
Troubleshooting
Summary and Next Steps
Requirements
- Hands-on experience with data analysis (e.g., using Excel)
- General understanding of database concepts
- No programming experience required
Audience
- Data analysts
35 Hours
Testimonials (3)
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.
Ian - Archeoworks Inc.
Course - ArcGIS Fundamentals
All the topics which he covered including examples. And also explained how they are helpful in our daily job.
madduri madduri - Boskalis Singapore Pte Ltd
Course - QGIS for Geographic Information System
The thing I liked the most about the training was the organization and the location
