Open Source Python Education Software
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Python Education Software
View 4187 business solutionsBrowse free open source Python Education Software and projects below. Use the toggles on the left to filter open source Python Education Software by OS, license, language, programming language, and project status.
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Zero Install is a decentralised cross-distribution software installation system. Create one package that works everywhere! With dependency handling and automatic updates, full support for shared libraries, and integration with native package managers
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Brain Workshop
Python implementation of the Dual N-Back mental exercise
Brain Workshop is a Python implementation of the Dual N-Back mental exercise. This exercise is the only mental activity that has been scientifically shown to improve your short-term memory (working memory) and fluid intelligence. -
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DrPython is a highly customizable cross-platform ide to aid programming in Python. It was developed with teaching in mind, and has a clean, simple interface. It is written in Python, using wxPython as the gui.
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Mnemosyne resembles a traditional flash-card program but with an important twist: it uses a sophisticated algorithm to schedule the best time for a card to come up for review.
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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eXe
eLearning XHTML editor
eXe, the eLearning XHTML editor, is a freely available authoring application that assists teachers in the publishing of web content without the need to become proficient in HTML or XML markup. Resources authored in eXe can be exported to the web or LMS. -
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Simulation of Urban MObility
SUMO is a microscopic, multi-modal traffic simulation.
SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians and comes with a large set of tools for scenario creation. The code and the issue tracker can be found at https://github.com/eclipse-sumo/sumo/ The documentation can be found at https://sumo.dlr.de/docs/ -
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eduActiv8
A collection of interactive educational exercises
eduActiv8 is a free Open Source multi-platform educational application that aims to assist in learning various early education topics - from learning the alphabet and new words, colours, time to a wide range of maths-related subjects. eduActiv8 is a continuation of the development of the pySioGame project just under a new name. It is being developed on GitHub at: https://github.com/imiolek-ireneusz/eduActiv8 but 'compiled' releases are published here. The latest version has been partially redesigned to improve usability, but certain activities will still be in the somewhat "prototype quality" - this will be gradually redesigned as time allows. Currently, it is available for Windows, MacOS, Linux and Android (you may need to allow unknown sources to install it on Android). Packages for multiple Linux distributions are available from: https://software.opensuse.org//download.html?project=home%3Aimiolek-i&package=eduactiv8 Support eduActiv8 at https://ko-fi.com/eduactiv8 -
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OpenTeacher is an opensource application that helps you learn a foreign language vocabulary. Just enter some words in your native and foreign language, and OpenTeacher tests you.
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Educational activities based on multimedia elements (images, sounds, and text). ie. associations, puzzles, counting activities... Creation and modification of the activities using XML files. Multiple language support, multiple screen resolutions (SVG
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GNU Solfege is *free* ear training software written in Python 3.4 using the Gtk+ 3 toolkit. The program is designed to be easily extended with lesson files (data files), so the user can create new exercises.
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Archivematica
Free and open-source digital preservation system
Archivematica is a web- and standards-based, open-source application which allows your institution to preserve long-term access to trustworthy, authentic, and reliable digital content. Our target users are archivists, librarians, and anyone working to preserve digital objects. You are free to copy, modify, and distribute Archivematica with attribution under the terms of the AGPLv3 license. Archivematica is an open-source application based on recognized standards that makes it possible to preserve long-term access to your institution's digital content. Archivematica is a set of free software tools that allow the user to process digital objects from the moment they are entered into the system until their publication according to the ISO-OAIS functional model. The user can monitor and control the ingestion and preservation of micro-services through the control panel. Archivematica uses standards such as METS, PREMIS, Dublin Core, and the BagIt specification. -
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If you are looking for the childsplay application please go to http://www.childsplay.mobi
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Python Tutorial
Xiaobai Python Tutorial
Python Tutorial is a Chinese beginner-friendly Python tutorial repository focused on practical self-study. It is written for learners who want to build programming fundamentals step by step instead of collecting scattered resources without a path. The course is based on Python 3.10+ and marks newer language features from Python 3.11, 3.12, and 3.13 where relevant. It offers both a document-style reading site and an interactive learning site where users can write code in the browser. The interactive version includes exercises, automatic judging, progress tracking, and unlockable lesson flow. The content covers basic syntax, code style, data types, variables, lists, tuples, dictionaries, sets, loops, functions, iterators, generators, and object-oriented programming. -
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Mastering Bitcoin
Mastering Bitcoin 3rd Edition - Programming the Open Blockchain
The bitcoinbook repository contains the source code for Mastering Bitcoin, the authoritative open-source book by Andreas M. Antonopoulos on Bitcoin and cryptocurrency technologies. Written in a collaborative and continuously updated format using Markdown and AsciiDoc, the book serves as a comprehensive technical guide for developers, engineers, and system architects who want to understand how Bitcoin works. It covers the protocol, cryptography, peer-to-peer architecture, wallets, mining, and application development. -
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AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. It can automatically generate code for experiments, run them in a sandbox environment, and analyze the results with statistical methods. The platform also uses multi-agent debate and automated peer review processes to refine research findings and improve paper quality. By combining literature discovery, experimentation, and writing automation, AutoResearchClaw aims to turn research ideas into conference-ready papers with minimal human intervention. -
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Brain Tokyo Workshop
Experiments and code from Google Brain’s Tokyo research workshop
The Brain Tokyo Workshop repository hosts a collection of research materials and experimental code developed by the Google Brain team based in Tokyo. It showcases a variety of cutting-edge projects in artificial intelligence, particularly in the areas of neuroevolution, reinforcement learning, and model interpretability. Each project explores innovative approaches to learning, prediction, and creativity in neural networks, often through unconventional or biologically inspired methods. The repository includes implementations, experimental data, and supporting research papers that accompany published studies. Notable works such as Weight Agnostic Neural Networks and Neuroevolution of Self-Interpretable Agents highlight the team’s exploration of how AI can learn more efficiently and transparently. Overall, this repository serves as an open research hub for sharing ideas and advancing the understanding of intelligent systems. -
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Claude How-To
A visual, example-driven guide to Claude Code
Claude How-To is a visual, example-driven guide for learning Claude Code. It covers basic concepts, memory, slash commands, hooks, skills, subagents, MCP configuration, plugins, and advanced agent workflows. The project is designed as a practical learning path rather than a simple list of notes. It includes copy-paste templates that users can apply directly to their own projects. The guide also uses diagrams and structured examples to explain not only how features work, but why they matter in a real development workflow. Its main value is helping developers move from casual Claude Code usage to more organized, automated, and agent-driven software development. -
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Megatron-LM
Ongoing research training transformer models at scale
Megatron-LM is a GPU-optimized deep learning framework from NVIDIA designed to train extremely large transformer-based language models efficiently at scale. The repository provides both a reference training implementation and Megatron Core, a composable library of high-performance building blocks for custom large-model pipelines. It supports advanced parallelism strategies including tensor, pipeline, data, expert, and context parallelism, enabling training across massive multi-GPU and multi-node clusters. The framework includes mixed-precision training options such as FP16, BF16, FP8, and FP4 to maximize performance and memory efficiency on modern hardware. Megatron-LM is widely used in research and industry for pretraining GPT-, BERT-, T5-, and multimodal-style models, with tooling for checkpoint conversion and interoperability with Hugging Face. Overall, it is a production-grade system for organizations pushing the limits of large-scale language model training. -
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Web Security Dojo
Virtual training environment to learn web app ethical hacking.
Web Security Dojo is a virtual machine that provides the tools, targets, and documentation to learn and practice web application security testing. A preconfigured, stand-alone training environment ideal for classroom and conferences. No Internet required to use. Ideal for those interested in getting hands-on practice for ethical hacking, penetration testing, bug bounties, and capture the flag (CTF). A single OVA file will import into VirtualBox and VMware. There is also an Ansible script for those brave souls that want transform their stock Ubuntu into a virtual dojo. Bow to your sensei! username: dojo password: dojo -
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Interpretable machine learning
Book about interpretable machine learning
This book is about interpretable machine learning. Machine learning is being built into many products and processes of our daily lives, yet decisions made by machines don't automatically come with an explanation. An explanation increases the trust in the decision and in the machine learning model. As the programmer of an algorithm you want to know whether you can trust the learned model. Did it learn generalizable features? Or are there some odd artifacts in the training data which the algorithm picked up? This book will give an overview over techniques that can be used to make black boxes as transparent as possible and explain decisions. In the first chapter algorithms that produce simple, interpretable models are introduced together with instructions how to interpret the output. The later chapters focus on analyzing complex models and their decisions. In an ideal future, machines will be able to explain their decisions and make a transition into an algorithmic age more human. -
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Advanced Trigonometry Calculator
Open-source C/C++ math engine for advanced scientific computing
Advanced Trigonometry Calculator (ATC) is an open-source mathematical computing engine written mainly in C/C++. Created in 2011 and maintained by Renato Alexandre dos Santos Freitas, ATC is designed as a practical Windows desktop application for advanced calculations, automation, and technical problem solving. ATC supports equation solving, polynomial tools, complex numbers, matrix calculations, statistics, physics, geometry, unit conversions, DSP/FFT operations, and scripting. It can also process batch TXT files, making it useful for repeatable calculations and automated workflows. The project also includes ATC Online Alpha, a WebAssembly-based version that brings parts of the ATC engine to the web. ATC is released under the GPLv3 license and is made in Portugal. -
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Concordia
Crowdsourcing platform for full text transcription and tagging
Concordia is a platform for crowdsourcing transcription and tagging of text in digitized images. It was developed by the Library of Congress so that volunteers of all backgrounds could transcribe and tag digitized images of manuscripts and typed materials from the Library’s collections that could not otherwise be done by optical character recognition. -
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Digital Forensics Guide
Learn all about Digital Forensics and Computer Forensics
The Digital Forensics Guide repository is a comprehensive, structured reference for investigators, analysts, students, and cybersecurity professionals interested in digital forensics principles, tools, methodologies, and workflows. It organizes foundational topics such as evidence acquisition, disk and memory analysis, file system structures, network forensics, artifact extraction, timeline generation, and reporting into digestible modules that help build core competency. Alongside conceptual explanations, the guide includes practical examples with widely used tools (like Autopsy, Volatility, Sleuth Kit, and network analysis suites), illustrating how investigations proceed from initial data capture to final analysis. The goal is to provide both a learning path and a quick reference for real-world casework, bridging the gap between academic theory and operational practice. -
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Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing what this book covers in general, I’d describe it as a comprehensive resource on the fundamental concepts of machine learning and deep learning. The first half of the book introduces readers to machine learning using scikit-learn, the defacto approach for working with tabular datasets. Then, the second half of this book focuses on deep learning, including applications to natural language processing and computer vision. -
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Neural MMO
Code for the paper "Neural MMO: A Massively Multiagent Game..."
Neural MMO is a massively multi-agent simulation environment developed by OpenAI for reinforcement learning research. It provides a persistent, procedurally generated world where thousands of agents can interact, compete, and cooperate in real time. The environment is inspired by Massively Multiplayer Online Role-Playing Games (MMORPGs), featuring resource gathering, combat mechanics, exploration, and survival challenges. Agents learn behaviors in a shared ecosystem that supports long-term training and emergent dynamics across large populations. The project is built to test scalability in multi-agent reinforcement learning, with features such as procedurally generated terrain and configurable game mechanics. While the original release has since been succeeded by newer versions maintained outside OpenAI, it remains a landmark framework for studying large-scale agent interactions in complex environments.