data-science

Asabeneh/30-Days-Of-Python

A 30-day, day-by-day curriculum covering Python basics to web and data tools — A structured, free course that walks beginners from variables and loops through OOP, web scraping, Pandas, Flask, and MongoDB in daily lessons. Useful for self-paced learners who want a clear roadmap plus optional video support rather than scattered tutorials.

pandas-dev/pandas

pandas: the Python data toolkit behind countless analyses — pandas is the long-running Python library for labeled, tabular data, offering DataFrame structures, alignment, and statistical tools modeled after R's data.frame. With active CI, NumFOCUS backing, and steady releases on PyPI/conda, it remains a foundational choice for data scientists and analysts working in Python.

SimplifyJobs/Summer2027-Internships

A daily-updated master list of Summer 2027 tech internships — Community-maintained by Pitt CSC and Simplify, this repo tracks over 1,800 Summer 2027 internships across software engineering, data science/AI, product management, quant finance, and hardware. Roles are categorized and updated daily via issue submissions, making it a go-to resource for students job-hunting early.

apache/airflow

Apache Airflow: Workflow Orchestration as Python DAGs — Airflow lets teams define, schedule, and monitor data pipelines as Python code, with dependencies expressed as DAGs. It's widely used for ETL, ML, and data integration tasks across many providers and backends. This is the mature, actively maintained Apache project behind countless production data pipelines.

ray-project/ray

Ray scales Python and ML workloads from laptop to cluster — Ray pairs a distributed runtime (tasks, actors, objects) with AI libraries for data, training, tuning, RL and serving. It runs anywhere from a laptop to Kubernetes clusters, and now includes LLM serving/inference tooling plus a distributed debugger and dashboard, making it relevant for teams scaling both classic ML and large language model workloads.

eriklindernoren/ML-From-Scratch

A readable NumPy library covering regression to deep learning basics — This repo reimplements classic ML and deep learning algorithms—regression, CNNs, GANs, reinforcement learning, genetic algorithms—using bare NumPy, prioritizing transparency over speed. It's aimed at learners who want to see the actual math and logic behind models rather than use optimized black-box libraries.

opengeos/GeoLibre

A privacy-first GIS app with 1,000+ browser-based WASM tools — GeoLibre is a free, cloud-native GIS platform built on Tauri, React, MapLibre GL JS and DuckDB-WASM. It runs in browsers, desktop, mobile and Jupyter, offers 1,000+ WebAssembly geoprocessing tools with no server needed, and lets users switch between MapLibre, Mapbox, CesiumJS or ArcGIS rendering engines in one project.

PriorLabs/TabPFN

A Foundation Model That Predicts Tabular Data in One Pass — TabPFN is a foundation model trained on synthetic data that classifies and regresses on real-world tabular datasets without per-dataset training, using a single forward pass. The latest TabPFN-3.5 architecture adds distribution embedding and cross-row attention, runs on modest GPUs (or CPU for smaller datasets), and offers free hosted inference via TabPFN Client for those without a GPU.

parrt/dtreeviz

Visual, interpretable decision trees across multiple ML libraries — dtreeviz renders decision trees and feature-space visualizations to help explain how tree-based models work. It supports scikit-learn, XGBoost, Spark MLlib, LightGBM, and TensorFlow decision forests, making it useful for anyone teaching, learning, or debugging tree-based machine learning models.

atsushi-green/ds-ai-coding-skills

Pre-built AGENTS.md skills to guide AI coding tools for data scientists — A collection of AGENTS.md router files, Claude/Codex skills, and prompts designed for data science workflows, covering Python, SQL, Polars, visualization, and statistics. It includes paired 'diagnostics' skills that force AI assistants to output standardized charts alongside analysis results, with a gallery of generated examples.

kobaltgit/StatCraft

A Safe-Rust SPSS Alternative That Also Speaks MCP — StatCraft is an open-source statistical package written in 100% Safe Rust, aimed at researchers, educators, and analysts who need an SPSS-like GUI without crashes or licensing costs. Notably, it ships an MCP bridge so AI agents can drive the GUI directly, making it a candidate tool for both human statisticians and automated analysis workflows.

ashtonckj/Purrrfessorrr-Slothhh

A Pixel-Art Office of Cats Automates Your EDA Boilerplate — This hackathon project turns routine exploratory data analysis into a themed workflow: upload a CSV/TSV/XLSX and five 'specialist cats' handle quality checks, charts, plain-English summaries, and reusable Python/R code. Statistics are computed deterministically; an optional Gemma model only explains results from a summary, never raw data or the math itself.

0227lia/data-science-portfolio

A student portfolio that keeps data science claims honest — This Astro/TypeScript static site presents six reproducible public-data case studies spanning data engineering, geospatial analysis, forecasting, operations research, NLP and ML. It explicitly separates observed results from modeled scenarios and sources all displayed metrics from committed runs in linked repos, useful for anyone evaluating a data science student's work critically.