Open Source Python Education Software - Page 3
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Python Education Software
View 4227 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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LangChain Open Deep Research
Fully open source deep research agent
Open Deep Research is a configurable, fully open-source agent for producing detailed research reports from complex questions. It separates work across models used for summarization, active research, information compression, and final report generation. Users can select from multiple language model providers as long as the chosen models support tool calling and structured outputs. Search can be powered by several APIs, native provider search, or external tools connected through MCP. The agent runs on LangGraph and can be explored locally through LangGraph Studio, an API, and generated API documentation. Environment settings control model choices, search services, MCP servers, and other research behavior. The repository also includes evaluation scripts for Deep Research Bench, enabling reproducible comparisons across difficult multilingual tasks. -
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List of Free Learning Resources
Freely available programming books
List of Free Learning Resources is a curated open-source collection of free programming resources, including books, tutorials, and courses across many languages and disciplines. Maintained by the community, it organizes materials by topic, language, and skill level, making it easy to discover learning resources. The repository includes content on software development, computer science, data science, and more. It is continuously updated with new resources contributed by developers worldwide. The project emphasizes accessibility and open education, providing high-quality materials without cost. It serves as a central hub for self-learners and professionals alike. Its structured organization makes it a widely used reference for learning programming. -
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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. -
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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. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Web Dev for Beginners
About 24 Lessons, 12 Weeks, Get Started as a Web Developer
Web-Dev-For-Beginners is Microsoft’s open source, project-based curriculum for learning web development from scratch. Designed as a 12-week, 24-lesson course, it covers HTML, CSS, and JavaScript fundamentals through hands-on projects like terrariums, browser extensions, and space games. Each lesson includes a mix of pre-lecture quizzes, written content, assignments, challenges, and post-lecture quizzes to reinforce learning. The course also offers global accessibility with translations in more than 40 languages and built-in support for running in GitHub Codespaces or locally in Visual Studio Code. This makes it a practical and engaging way for beginners to gain a solid foundation in web development. -
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WorkBuddyGuide
A practical, open-source guide to mastering WorkBuddy
WorkBuddy Guide is a community-maintained, open-source practical handbook for learning WorkBuddy through real workplace scenarios. Rather than restating product documentation, it follows tasks from initial setup through repeatable team workflows. The guide covers installation, interface basics, Skills, connectors, APIs, automation, knowledge management, content work, meetings, remote work, and other use cases. Advanced sections address building Skills, multi-agent system design, automation reliability, permissions, acceptance criteria, and fallback planning. Role- and industry-oriented chapters help readers adapt WorkBuddy to different professional contexts. The VitePress website adds full-text search, navigation, dark mode, flowcharts, and mobile support, while community cases provide reusable examples. -
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codex-orange-book
A Full-Link Guide to Using Codex from Installation to Real-World Cases
codex-orange-book is an unofficial open-source guide for learning and applying Codex in real software workflows. It is written as a full learning resource rather than a conventional software package. The guide covers installation, configuration, core concepts, standard workflows, practical examples, and extension paths. It explains Codex App, Codex CLI, Codex IDE Extension, Codex Web, cloud workflows, Skills, MCP, Git, GitHub, automation, and memory-related usage. It is aimed at developers, independent builders, AI tool users, and technical teams that want a structured way to adopt Codex. Overall, it functions as a practical handbook for moving from basic Codex setup to real project execution and review-ready deliverables. -
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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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PythonCard is a GUI construction kit for building cross-platform desktop applications on Windows, Mac OS X, and Linux, using the Python language.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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KaNaPi
Educational Linux Distribution
Main goals: * Prepare operating system based on Linux kernel and free software for use at home from scratch by building sources. Binary packages/images are also available. * Each package is installed in separate directory, so you can use different versions of applications and libraries by design. * There is only one user 'kanapi' with root permissions, so you don't have to login, remember passwords, etc. * Simple configuration * Automatic compilation. -
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pySioGame / eduActiv8
Educational Activities for Kids
The pySioGame project has been renamed to eduActiv8 - please visit the new project page at https://sourceforge.net/projects/eduactiv8/ More info available at http://www.eduactiv8.org Packages for multiple Linux distributions of eduActiv8 are available from: https://software.opensuse.org//download.html?project=home%3Aimiolek-i&package=eduactiv8 -
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GGI stands for "General Graphics Interface", and it is a project that aims to develop a reliable, stable and fast graphics system that works everywhere. We want to allow any program using GGI to run on any platform requiring at most a recompile.
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PowerTalk automatically speaks Microsoft PowerPoint presentations. For presenters who find speaking difficult, audiences containing people with visual impairments and fun educational uses. Uses synthesised computer speech provided with Windows
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Childsplay is at http://www.childsplay.mobi Childsplay is a 'suite' of educational games for young children. It's written in Python and uses the SDL-libraries to make it more games-like then, for instance, gcompris. The aim is to be educational and at the same time be fun to play.
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100 Days of Code YouTube
Source code for 100 days of code python course on YouTube
100 Days of Code YouTube is a day-by-day source-code collection for a comprehensive Python programming course. The repository organizes lessons into numbered folders that progress from basic concepts to advanced language features. Early material covers variables, data types, input, strings, conditions, loops, functions, and common collections. Intermediate lessons explore exceptions, modules, file I/O, functional programming, and extensive object-oriented programming concepts. Later days introduce command-line utilities, generators, regular expressions, AsyncIO, multithreading, and multiprocessing. Exercises and solution days are distributed throughout the sequence so learners can repeatedly apply what they have studied. -
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A Machine Learning Course with Python
A course about machine learning with Python
The purpose of this project is to provide a comprehensive and yet simple course in Machine Learning using Python. Machine Learning, as a tool for Artificial Intelligence, is one of the most widely adopted scientific fields. A considerable amount of literature has been published on Machine Learning. The purpose of this project is to provide the most important aspects of Machine Learning by presenting a series of simple and yet comprehensive tutorials using Python. In this project, we built our tutorials using many different well-known Machine Learning frameworks such as Scikit-learn. In this project you will learn what is the definition of Machine Learning? When it started and what is the trending evolution? What are the Machine Learning categories and subcategories? What are the mostly used Machine Learning algorithms and how to implement them? -
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Ansible Automation Platform Workshops
Training course for Ansible automation platform
The Red Hat Ansible Automation Workshops project is intended for effectively demonstrating Ansible's capabilities through instructor-led workshops or self-paced exercises. These interactive learning scenarios provide you with a pre-configured Ansible Automation Platform environment to experiment, learn, and see how the platform can help you solve real-world problems. The environment runs entirely in your browser, enabling you to learn more about our technology at your pace and time. The demos are intended for effectively demonstrating Ansible capabilities with prescriptive guides on the Ansible Automation Workshop infrastructure. Check out the optional website which is rendered automatically from markdown files using Github Pages. -
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Linux insides
A book-in-progress about the Linux kernel and its insides
Linux insides is an extensive open-source educational book project that explores the internal architecture and behavior of the Linux kernel. The repository contains a structured series of chapters that explain low-level topics such as booting, memory management, interrupts, system calls, and synchronization primitives. The project’s stated goal is to share knowledge about Linux kernel internals and related low-level concepts in an accessible narrative format. It is written for readers who already have some familiarity with C and assembly language and want to understand what happens under the hood of Linux. The material is continuously updated as the kernel evolves, reflecting changes in modern kernel versions. Overall, linux-insides is widely regarded as a deep technical learning resource for systems programmers and advanced Linux enthusiasts. -
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Recommenders
Best practices on recommendation systems
The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several state-of-the-art algorithms are included for self-study and customization in your own applications. Please see the setup guide for more details on setting up your machine locally, on a data science virtual machine (DSVM) or on Azure Databricks. Independent or incubating algorithms and utilities are candidates for the contrib folder. This will house contributions which may not easily fit into the core repository or need time to refactor or mature the code and add necessary tests. -
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Scientific Visualization
An open access book on scientific visualization using python
The Scientific Visualization book is a freely available open-access textbook that introduces how to produce effective scientific visualizations using Python, focusing especially on leveraging the popular plotting library Matplotlib (and related tools). It goes beyond simple plotting tutorials and emphasizes design principles: how to choose colors, layout subplots, annotate graphs, and present data in a way that is both accurate and visually compelling. As such, it serves as a guide for researchers, data scientists, and academic authors who need to create publication-quality figures or explanatory graphics, rather than quick exploratory plots. It includes extensive examples that demonstrate best practices — for instance handling multiple subplots, combining line plots with scatter/density overlays, or rendering high-resolution vector graphics for print. -
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The Art of Programming
A collection of practical tips can be found at the bottom of this page
The Art of Programming (Second Edition) is a curated collection of programming problems and solutions originally derived from the Microsoft 100 Interview Questions blog series, later refined into a long-running tutorial and ultimately a published book. Created by July, the series began in 2010 and has since evolved into an in-depth exploration of algorithmic thinking, data structures, and coding interview preparation. The repository brings together 42 classic programming problems from the original series, enhanced with detailed explanations, formula derivations, and optimized solutions. In July 2023, work on the second edition was announced, which expands the project with updated content, new problems inspired by recent big-tech interviews, and introductions to modern machine learning techniques such as XGBoost, CNNs, RNNs, and LSTMs. This collection serves both as a historical record of algorithm problem-solving and as a living resource for programmers preparing for interviews. -
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US Job Market Visualizer
A research tool for visually exploring Bureau of Labor Statistics
US Job Market Visualizer is a research tool for interactively exploring Occupational Outlook Handbook data from the U.S. Bureau of Labor Statistics. It organizes information for 342 occupations into a treemap where area represents employment and color can represent different metrics. Users can compare projected growth, median pay, education requirements, and estimated digital AI exposure. The repository includes tools for scraping BLS pages, converting them to structured data, and building the visualization dataset. An LLM scoring pipeline can evaluate occupations using custom criteria supplied through prompts. The included AI exposure layer is intended as an exploratory estimate rather than a prediction of job elimination. A generated prompt file also packages the complete dataset for data-grounded analysis with language models. -
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python-tutorial
Practical Python tutorials, including Python basics
python-tutorial is a practical Python learning repository that collects examples for everyday programming tasks. It covers Python fundamentals, advanced language features, object-oriented programming, multithreading, databases, data science, Flask development, web crawling, and utility scripting. The project is intended for beginners learning Python and for working developers who want reference implementations for common scripts. Its examples are tested in a Python 3 environment and organized into topic-based directories. The repository also includes notebook-style learning materials for basic data types and core language concepts. It is useful as a structured self-study resource, classroom supplement, or quick reference for practical Python usage. -
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VPython
This project is no longer active. See vpython.org.
This project is no longer active. See vpython.org.
