Sample project to demonstrate data engineering best practices

A collection of learning resources for curious software engineers

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 👇🏼

Solution for IBM Data Engineering Professional Certificate

An ongoing list of pandas quirks

A guide for technical professionals looking to start consulting

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

All the resources you need to get to Senior Engineer and beyond

Robust, production worthy, ready to go Jupyter Notebooks

Summary of the book The Pragmatic Programmer by Andrew Hunt and David Thomas

Full reference of LinkedIn answers 2024 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel t…

ePorezi application mod to run on MacOS/Linux

an online-shopping platform database, course project for COMP421@McGill

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Third capstone for Springboard data science career track focused on an SEO business problem related to Dunkin Donuts.

Solutions for #8WeekSQLChallenge using SQL Server.

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

Practical machine learning notebook & articles covers the machine learning end to end life cycle.

Examples of matplotlib codes and plots

A topic-centric list of HQ open datasets.

A/B Testing — A complete guide to statistical testing

Sample of data analysis done using SQL

Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017

Collection of useful data science topics along with articles, videos, and code

[Legacy] Data & AI Notebook templates catalog organized by tools, following the IMO (input, model, output) framework for easy usage and discovery..

Assorted exercises and proof-of-concepts to understand and study machine learning and statistical learning theory

My personal GitHub Page, with a customized Jekyll theme.

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.