30 open-source projects similar to karlhorky/learn-to-program, ranked by shared indexed features. Tags may describe platforms or build tools rather than the same primary purpose. Check each project’s use case, license, and deployment requirements before treating it as a replacement.
This project is a community-maintained directory that serves as a comprehensive index of software tools, frameworks, and educational materials. It functions as an open-source knowledge base, organizing diverse engineering domains and technical resources into a structured taxonomy to assist developers in discovering high-quality content. The directory distinguishes itself through a decentralized peer-review model, where independent contributors curate, verify, and update entries to ensure accuracy and relevance. All information is stored in a version-controlled, flat-file markdown format, whic
A tiny list limited to the best JavaScript Learning Resources
Platforms, tools, and guides for critical organizers 🌆
Resources about public speaking
🚀 A curated list of awesome resources for product/program managers to learn and grow.
Curated list of 20,000+ hours and 200+ free courses with certificates in IT, CS, Design and Business.
An awesome list of resources for specific science, technology, engineering, art, and math (STEAM) classes that students and teachers can use to supplement their learning
Training materials crafted and publicly provided by Red Naga members
This project is a comprehensive, open-source educational curriculum designed to guide developers through the mastery of generative artificial intelligence. It provides a structured learning path that covers foundational concepts, prompt engineering, and the practical application of large language models. The repository serves as a central hub for skill acquisition, offering sequential modules that progress from basic model mechanics to advanced architectural patterns. The curriculum distinguishes itself by focusing on the end-to-end lifecycle of intelligent software, including the implementat
This project is a comprehensive educational curriculum and engineering handbook focused on the lifecycle of large language models. It serves as a structured knowledge base for machine learning practitioners, covering the fundamental mathematical and architectural principles of transformer-based sequence modeling, as well as the practical implementation of supervised instruction fine-tuning and preference-based model alignment. The repository distinguishes itself by providing a deep dive into advanced model composition and optimization techniques. It details methodologies for weight-space mode
This repository serves as an educational framework for building large language models from the ground up. It provides a structured curriculum that guides learners through the end-to-end lifecycle of model development, including data processing, architecture design, and optimization. By focusing on low-level implementation, the project enables users to master the fundamental mechanics of artificial intelligence without relying on high-level abstraction frameworks. The project distinguishes itself by constructing neural network components and gradient-based optimization logic from first princip
List of Elixir books
:books: A collection of awesome resources for technical book authors
Curated tutorials and resources for Large Language Models, AI Painting, and more.
This project serves as a comprehensive technical reference and educational platform for the Ethereum ecosystem. It provides a deep dive into the fundamental architecture of decentralized ledger systems, covering the core mechanisms that enable trustless state transitions, cryptographic security, and network consensus. The documentation distinguishes itself by bridging high-level conceptual frameworks with practical implementation details. It details the lifecycle of smart contract development, from source code compilation and bytecode analysis to deployment and interaction patterns. Furthermo
The CppCoreGuidelines is a comprehensive software engineering standard that provides a curated framework of coding conventions and design principles for C++. It serves as an authoritative guide for writing safe, efficient, and maintainable code by establishing high-level architectural patterns and organizational principles for large-scale projects. The guidelines emphasize the use of a strong, static type system to ensure memory safety and enforce consistent resource management patterns. The project distinguishes itself by promoting the zero-overhead abstraction principle, ensuring that high-
This project is a data science curriculum and instructional syllabus designed to teach the fundamental principles and tools of the field. It provides a structured set of learning materials, including R programming courseware and guides for statistical learning. The materials focus on the practical application of data science, covering data cleaning, visualization, and exploratory data analysis. It includes resources for mastering specific techniques such as linear regression, classification, and unsupervised learning. The curriculum is organized into a modular sequence of educational modules
This project is a comprehensive collection of machine learning educational resources, featuring a Python-based curriculum, study guides for deep learning, and a specialized knowledge base for machine learning operations. It provides structured learning paths that guide users from foundational programming through to advanced neural network implementations. The repository focuses on interactive learning by providing a directory of executable notebooks and cloud-hosted experiments. It maps theoretical research papers and textbooks to practical code implementations and maintains a curated directo
This project is a comprehensive technical reference and educational resource designed to improve proficiency with command-line interfaces. It functions as a productivity toolkit, providing a structured knowledge base of essential terminal operations, system administration tasks, and high-impact command sequences for daily development workflows. The guide distinguishes itself through its cross-platform approach, offering standardized documentation that maps utility usage across Linux, macOS, and Windows environments. It provides specific guidance for managing native tools and compatibility lay
This project is a comprehensive framework for the training, fine-tuning, and deployment of large language models. It functions as a distributed deep learning platform that enables users to scale model workflows across multiple hardware nodes while providing tools for model evaluation and performance benchmarking. The platform distinguishes itself by offering specialized utilities for model compression and weight transformation, allowing users to reduce memory footprints and latency through quantization and pruning. It supports the adaptation of large models for consumer-grade hardware, facili
Mastering Bitcoin is a technical book that explains what Bitcoin is and how it works.
Podcast about Android Development with Hannes Dorfmann, Artem Zinnatullin, Artur Dryomov and wonderful guests!
This project is a technical learning resource and developer knowledge base focused on the integration of large language models into software applications. It provides a structured collection of guides and code examples designed to teach developers how to implement intelligent features using proven patterns and best practices. The repository distinguishes itself through a library of functional demonstrations that cover complex topics such as retrieval-augmented generation, function calling, and prompt engineering workflows. These materials are organized into a modular structure, allowing for t
LLM-RL-Visualized is a visual reference library and collection of knowledge maps designed to explain Large Language Model and Reinforcement Learning algorithms. It provides a structured system of conceptual diagrams and taxonomies covering the intersection of language model alignment and reinforcement learning. The project distinguishes itself through detailed visual mappings of complex workflows, such as the coordination of reward models and policy optimization in reinforcement learning from human feedback. It contrasts different preference optimization architectures, such as RLHF and Direct
This project is a centralized, open-access repository that serves as a structured directory for technical education and professional development. It functions as a community-driven knowledge base, aggregating high-quality learning materials to support global accessibility to computer science and software engineering resources. The platform distinguishes itself through a collaborative governance model that utilizes peer-reviewed workflows for all content additions and modifications. By leveraging structured text files and decentralized version control, the repository maintains a searchable, hu
Curated list: Resources for machine learning in Ruby
A list of programming tutorials in which aspiring software developers learn how to build an application from scratch. These tutorials are divided into different primary programming languages. Tutorials may involve multiple technologies and languages.