Search Results for "ai coding for beginners"
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Showing 8 open source projects for "ai coding for beginners"
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Generative AI for Beginners .NET
Hands-on .NET course for building real-world generative AI apps
Generative AI for Beginners .NET is a hands-on course that helps developers build real-world AI applications using the .NET ecosystem. It walks through core concepts such as text generation, chat-based interactions, and integrating large language models into applications. Each lesson includes short videos, working code samples, and step-by-step instructions, making it easy to follow and apply immediately. -
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MiniMax Skills
Development skills for AI coding agents
MiniMax skills is a modular system designed to provide structured development capabilities for AI coding agents, enabling them to perform complex engineering tasks with guided workflows and domain-specific knowledge. It defines a set of reusable “skills” that encapsulate best practices, architectural patterns, and step-by-step processes for building applications across multiple platforms. These skills can be integrated into AI tools to improve the quality and consistency of generated code, particularly in areas such as frontend development, backend systems, mobile applications, and multimedia processing. ... -
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Unity MCP
AI-powered bridge connecting LLMs and advanced AI agents
Unity-MCP is an open-source integration that connects artificial intelligence assistants with the Unity game development environment through the Model Context Protocol. The project enables AI tools such as coding assistants and autonomous agents to interact directly with Unity projects, allowing them to analyze scenes, modify assets, and generate code within the development environment. By exposing Unity editor functionality through MCP tools, the plugin allows external AI systems to understand the structure of a game project and manipulate it programmatically. ... -
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MCP for Unity
AI bridge enabling assistants to control and automate Unity Editor
Unity MCP is an open source integration that connects AI assistants with the Unity Editor through the Model Context Protocol (MCP). It acts as a bridge that allows language models and AI coding tools to interact directly with a Unity development environment using structured commands and tools. By linking an AI assistant to a running Unity project, the system enables automated operations such as managing project assets, modifying scenes, editing scripts, and performing other development tasks inside the editor. ... -
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SwarmUI
Modular AI image and video generation web UI with extensible tools
SwarmUI is a modular web-based user interface designed for AI-driven image generation, with a strong focus on usability, performance, and extensibility. It serves as a unified environment for working with multiple AI models, including Stable Diffusion and newer image and video generation systems, allowing users to create and manage outputs through a browser interface. SwarmUI is built to accommodate both beginners and advanced users by offering a simple “Generate” interface alongside more advanced workflow tools that expose deeper configuration options. ... -
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Clean Code concepts for .NET/.NET Core
Clean Code concepts and tools adapted for .NET
...The repository covers topics such as naming conventions, code structure, error handling, and design patterns, emphasizing readability and long-term maintainability. It encourages developers to adopt disciplined coding habits that reduce technical debt and improve collaboration within teams. The content is structured in a way that allows both beginners and experienced developers to benefit from practical insights and actionable recommendations. It also highlights common pitfalls and anti-patterns, helping developers avoid mistakes in real-world scenarios. -
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Unity ML-Agents Toolkit
Unity machine learning agents toolkit
...To create intelligent behaviors, developers have had to resort to writing tons of code or using highly specialized tools. With Unity Machine Learning Agents (ML-Agents), you are no longer “coding” emergent behaviors, but rather teaching intelligent agents to “learn” through a combination of deep reinforcement learning and imitation learning. Using ML-Agents allows developers to create more compelling gameplay and an enhanced game experience. Advancement of artificial intelligence (AI) research depends on figuring out tough problems in existing environments using current benchmarks for training AI models. ... -
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...The interface is available in 18 languages. Features • 3 Translation Modes: Fluent (parallel), Area (overlay), Full Screen (smart detection) • Speaker detection with color-coding • Glint AI custom terminology control • Game-based profile system • Advanced settings with 50+ parameters for fine-tuned control • Share and import custom profiles (.glint) between users • Low CPU/RAM usage, optimized for Windows 10/11 Live Subtitle (Real-Time Voice Translation) Real-time speech-to-text translation for games, movies, and voice chats. ...
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