Feb. 20, 2024, 8:51 p.m. | Quentin Gallea, PhD

Towards Data Science - Medium towardsdatascience.com

The ultimate self-study guide for all levels

Image by author

While everyone focuses on AI and predictive inference, standing out requires mastering not just prediction, but understanding the “why” behind the data — in other words, mastering causal inference.

You have heard that “correlation does not imply causation”, but few truly grasp its implications or know when to confidently assert causality.

The distinction between predictive inference and causal inference is profound, with the latter often overlooked, leading to costly …

causal inference causality econometrics getting-started statistics

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US