Getting Started
Welcome to CAIS! This section will help you get up and running with the Causal AI Scientist quickly and efficiently.
New to causal inference? Start with our Your First Causal Analysis guide to understand the basics. If you’re already familiar with causal inference concepts, jump straight to the Quickstart Tutorial tutorial.
Getting Started Guide
- Installation Guide
- Quickstart Tutorial
- Overview
- Prerequisites
- Step 1: Setup and Configuration
- Step 2: Prepare Your Data
- Step 3: Run Your First Analysis
- Step 4: Understanding the Results
- Step 5: Exploring Different Queries
- Step 6: Working with Your Own Data
- Common Use Cases
- Understanding Method Selection
- Next Steps
- Troubleshooting Quick Fixes
- Your First Causal Analysis
What You’ll Learn
How to install CAIS in different environments (pip, conda, Docker)
Setting up API keys and configuration
Your first causal analysis in under 10 minutes
Understanding CAIS output and interpretation
Validating and troubleshooting your analyses
Best practices for causal inference with CAIS
Prerequisites
Basic Python knowledge
Familiarity with pandas DataFrames
Understanding of your research question and data structure
Next Steps
After completing the getting started guide, explore:
User Guide - Detailed usage patterns and configuration
Tutorials & Examples - Hands-on tutorials with real datasets
Causal Inference Methods - Understanding different causal inference methods