This is a repo with links to everything you'd ever want to learn about data engineering

Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼

Free MLOps course from DataTalks.Club

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

Python interactive dashboards for learning data science

An introduction to network analysis and applied graph theory using Python and NetworkX

Brushing and linking for big data

Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook

Open source book about making Python packages.

A tutorial for setting an SQL code generator with the OpenAI API

AutoML for causal inference.

Scikit-learn compatible decision trees beyond those offered in scikit-learn

⭕️ Data Engineering for Data Scientists

Repository fo Data Engineering Course

Integrated tool for model development and validation

Using SimPy to create OB patient flow models

Decomposing Global AUC into Cluster-Level Contributions for Localized Model Diagnostics

OB simulation metamodeling research project

IPython notebooks, R markdown docs, data, other stuff from tutorial blog posts on hselab.org

NHANES-GCP: Leveraging the Google Cloud Platform and BigQuery ML for reproducible machine learning with data from the National Health and Nutrition Examination Survey

Komodo Health's submission to the 2022 ACIC Causality Data Challenge

An exploration of first baseman receiving for the 2023 SMT Data Challenge

A personal reference for common actions in different languages and frameworks