Open Source Python Education Software for Windows - Page 2
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Python Education Software for Windows
View 747 business solutionsBrowse free open source Python Education Software for Windows and projects below. Use the toggles on the left to filter open source Python Education Software for Windows by OS, license, language, programming language, and project status.
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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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Think Python 2
LaTeX source and supporting code for Think Python, 2nd edition
ThinkPython2 is the repository for the second edition of Allen Downey’s Think Python textbook, which teaches programming fundamentals in Python to beginners. The code includes all of the example programs, exercises, and supplementary files referenced in the book, allowing learners to run the examples, experiment, and extend them. The repository contains clean, well-commented Python scripts that are easy to follow and map directly to chapters of the text, covering topics like variables, control flow, functions, recursion, data structures (lists, dictionaries), classes and objects, file I/O, and algorithmic thinking. It also contains solutions or hints for many exercises so learners can check their work or explore alternative implementations. Because it’s educational, the repository emphasizes readability, clarity, and progressive learning rather than performance tuning or advanced constructs. -
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nanoGPT
The simplest, fastest repository for training/finetuning models
NanoGPT is a minimalistic yet powerful reimplementation of GPT-style transformers created by Andrej Karpathy for educational and research use. It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare or custom corpora. It emphasizes readability and clarity: the training loop is cleanly written, and the code avoids heavy abstractions, letting students follow the architecture step by step. While simple, it can still train non-trivial models on modern GPUs and generate coherent text. The project has become widely used in tutorials, courses, and experiments for people learning how transformers work under the hood. -
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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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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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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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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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A library of tools for doing computation in game theory.
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8 Monitoring Tools in One APM. Install in 5 Minutes.AppSignal works out of the box for Ruby, Elixir, Node.js, Python, and more. 30-day free trial, no credit card required.
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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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DeepLearning
Deep Learning (Flower Book) mathematical derivation
" Deep Learning " is the only comprehensive book in the field of deep learning. The full name is also called the Deep Learning AI Bible (Deep Learning) . It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. Finally, the Deep Learning book provides research directions covering theoretical topics including linear factor models, autoencoders, representation learning, structured probabilistic models, etc. -
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DevOps Exercises
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git
DevOps Exercises is a massive, community-maintained collection of questions, tasks, and mini-challenges that cover the breadth of modern DevOps and platform engineering. It spans Linux, networking, Docker, Kubernetes, CI/CD, monitoring, cloud providers, security, and even soft skills and troubleshooting. The idea is to give candidates and teams a realistic practice ground for interviews, certifications, and day-to-day operational work. Because it’s structured as Q&A and exercises, you can go through it progressively or dip into specific domains where you need strengthening. The repository gets frequent contributions, keeping it aligned with current tooling and practices. It is widely used by people preparing for DevOps roles because it mirrors the style and depth of questions companies actually ask. -
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Google Open Source Project Style Guide
Chinese version of Google open source project style guide
Each larger open source project has its own style guide, a series of conventions on how to write code for the project (sometimes more arbitrary). When all the code maintains a consistent style, it is more important when understanding large code bases. easy. The meaning of "style" covers a wide range, from "variables use camelCase" to "never use global variables" to "never use exceptions". The English version of the project maintains the programming style guidelines used in Google. If the project you are modifying originates from Google, you may be directed to the English version of the project page to understand the style used by the project. The Chinese version of the project uses reStructuredText plain text markup syntax, and uses Sphinx to generate document formats such as HTML / CHM / PDF. -
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ML for Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
ML-For-Beginners is a structured, project-driven curriculum that teaches foundational machine learning concepts with approachable math and lots of code. Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. The repository includes quizzes, solutions, and instructor materials to make the content usable in classrooms or self-study. It emphasizes ethical considerations and model evaluation—accuracy is not the only metric—so students learn to validate and communicate results responsibly. By the end, participants can build end-to-end ML experiments, interpret outputs, and iterate with confidence rather than just copying code. -
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Tensorflow and deep learning
A crash course in six episodes for software developers
Tensorflow and deep learning repository is an educational deep learning crash course designed to help software developers quickly understand and apply machine learning concepts without requiring advanced academic background. It is structured as a series of guided lessons that combine theoretical explanations, practical examples, and runnable code, allowing learners to build intuition while actively experimenting with models. The repository covers core neural network concepts such as weights, biases, activation functions, and gradient descent, as well as more advanced techniques like convolutional networks, recurrent networks, and reinforcement learning. It includes multiple hands-on projects, such as handwritten digit recognition, airplane detection in images, and text generation using recurrent neural networks, which demonstrate how different architectures solve real-world problems. -
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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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data-science-on-gcp
Source code accompanying book: Data Science on the GCP
The data-science-on-gcp repository is a comprehensive collection of code examples and end-to-end workflows that accompany the book Data Science on the Google Cloud Platform, designed to teach developers how to build scalable data science and machine learning systems using Google Cloud services. It provides structured, chapter-aligned implementations that guide users through the full lifecycle of a data science project, including data ingestion, storage, processing, analysis, model training, and deployment. The repository is organized into multiple directories that reflect real-world pipelines, such as ingesting data, running SQL-based analytics, streaming data processing, using Spark and Dataproc, applying BigQuery ML, and deploying models with Vertex AI. It emphasizes practical, production-oriented workflows rather than isolated examples, showing how different Google Cloud services interact to form cohesive pipelines. -
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ety
A Python module to discover the etymology of words
ety is a Python library and command-line tool designed to explore and retrieve the etymological origins of words by analyzing linguistic data and relationships between languages. It allows users to query a word and obtain its historical roots, including intermediate forms across different languages and time periods. The tool can generate recursive etymology chains as well as tree structures that visually represent how a word evolved over time. It is built as both a reusable module and a CLI utility, making it suitable for integration into other applications or standalone use. The project relies on structured datasets that map relationships between words and languages, enabling systematic exploration of linguistic evolution. It is particularly useful for developers, linguists, and researchers interested in historical language patterns and word origins. -
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jieba
Stuttering Chinese word segmentation
"Jaba" Chinese word segmentation, do the best Python Chinese word segmentation component. Four word segmentation modes are supported. Precise mode, which tries to cut the sentence most precisely, suitable for text analysis. Full mode, scans all the words that can be formed into words in the sentence, the speed is very fast, but the ambiguity cannot be resolved. The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable for word segmentation in search engines. The paddle mode uses the PaddlePaddle deep learning framework to train the sequence labeling (bidirectional GRU) network model to achieve word segmentation. Also supports part-of-speech tagging. To use paddle mode, you need to install paddlepaddle-tiny, pip install paddlepaddle-tiny==1.6.1. Currently paddle mode supports jieba v0.40 and above. For versions below jieba v0.40, please upgrade jieba, pip install jieba --upgrade. -
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Advanced Trigonometry Calculator
Precision Trigonometry: Advanced Calculator for Complex Math
Advanced Trigonometry Calculator is equipped with a user-friendly interface that allows for easy input of problems and instant computation. Professionals such as engineers who need to perform advanced trigonometric calculations in their work will find this tool extremely useful. ATC Online Alpha: https://advantrigoncalc.sourceforge.io/atc/ More info by clicking below: https://advantrigoncalc.sourceforge.io/ Advanced Trigonometry Calculator was only and always only developed by the Portuguese Renato Alexandre dos Santos Freitas. Also author of poems, reflections and thoughts published on the platform https://www.pensador.com/autor/renato_alexandre_dos_santos_freitas/ ATC is Made in Portugal. He was born in Coimbra on July 6, 1991. He has a degree in Electrical and Telecommunications Engineering and began developing ATC at the beginning of his undergraduate studies. He works for Miclearning, Lda since April 2020. Providing services to Multimac Hito Innovation. -
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Geophar
Le couteau suisse du prof de maths
Calculatrice graphique avancée en français, destinée aux professeurs ou aux étudiants du collège et du lycée. Elle permet de faire du calcul approché, de tracer des courbes et des figures géométriques exportables en png, eps, pdf ou svg. Linux, Windows, Mac. Elle contient également un outil pour générer très facilement des tableaux de variations et de signes en LaTeX. -
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A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
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A cross-platform, open source software toolkit for authoring, managing and delivering e-learning via computer or the Internet.
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Network Simulator (fork CORE - Live USB)
Live DVD with CORE network simulator
The Common Open Research Emulator (CORE) is a tool for emulating networks on one or more machines. You can connect these emulated networks to live networks. CORE consists of a GUI for drawing topologies of lightweight virtual machines, and Python modules for scripting network emulation. -
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VPython
This project is no longer active. See vpython.org.
This project is no longer active. See vpython.org.
