Best AI tools for< Improve Coding Practices >

ICD AI is an advanced artificial intelligence tool designed to assist healthcare professionals in accurately assigning diagnostic codes to patient records. The tool utilizes machine learning algorithms to analyze medical data and suggest appropriate ICD codes, streamlining the coding process and reducing errors. With its user-friendly interface and robust features, ICD AI is revolutionizing medical coding practices and improving efficiency in healthcare facilities.

BugFree.ai is an AI-powered platform designed to help users practice system design and behavior interviews, similar to Leetcode. The platform offers a range of features to assist users in preparing for technical interviews, including mock interviews, real-time feedback, and personalized study plans. With BugFree.ai, users can improve their problem-solving skills and gain confidence in tackling complex interview questions.

AIgrind is a comprehensive coding platform designed to enhance AI and ML skills through a combination of practice, mentorship, job interview preparation, contests, and streak incentives. Users can engage with coding and theoretical questions, receive personalized mentorship from industry experts, prepare for job interviews with real questions, and participate in contests to track progress. The platform offers dual language support, a robust testing environment with extensive test case coverage, real-time feedback, and detailed performance analysis to help users improve their coding skills and knowledge for real-world applications.

FavTutor AI Learning is an AI-powered tool designed to help users master programming skills through personalized learning experiences. The tool utilizes artificial intelligence algorithms to provide tailored lessons, practice exercises, and feedback to enhance the user's programming proficiency. With FavTutor AI Learning, users can improve their coding abilities at their own pace and convenience, making it an ideal platform for both beginners and experienced programmers seeking to enhance their skills.

Pgrammer is an AI-powered platform designed to help users practice coding interview questions with personalized hints and analysis. Unlike traditional methods like LeetCode, Pgrammer offers a diverse set of questions for over 20 programming languages, real-time hints, and solution analysis to enhance users' coding skills and confidence. The platform utilizes AI, specifically GPT-4, to provide a tailored learning experience and feedback to users, ensuring they are well-prepared for coding interviews.

Cipher is an AI tool designed to help users prepare for coding interviews. It offers AI assistance to enhance interview preparation by providing personalized guidance and feedback. With Cipher, users can practice coding problems, receive hints and solutions, and improve their problem-solving skills. The platform aims to simulate real interview scenarios to boost confidence and performance. By leveraging AI technology, Cipher adapts to users' learning pace and offers tailored recommendations to address their weaknesses effectively.

Upsend is an AI-powered platform designed to help software engineering candidates prepare for technical interviews. It offers mock coding interviews with personalized feedback to enhance interview performance and increase job offer conversion rates. With industry-standard metrics and actionable insights, Upsend aims to simulate real interview scenarios and provide a comprehensive preparation experience for candidates.

CodeSignal is an AI-powered platform that helps users discover and develop in-demand skills. It offers skills assessments and AI-powered learning tools to help individuals and teams level up their skills. The platform provides solutions for talent acquisition, technical interviewing, skill development, and more. With features like pre-screening, interview assessments, and personalized learning, CodeSignal aims to help users advance their careers and build high-performing teams.

The Software Engineer Interview Questions Generator is an AI-powered tool that helps software engineers prepare for interviews by generating a wide range of technical questions related to various programming languages, frameworks, databases, and cloud services. Users can select specific topics of interest and customize the number of questions to generate. The tool leverages advanced natural language processing capabilities to provide relevant and challenging interview questions, making it a valuable resource for job seekers in the tech industry.

Tutory, formerly known as Persona, is an AI-powered educational platform that introduces Dahlia, a conversational AI system designed to tutor students in Math, Science, Computer Science, and English. Dahlia offers personalized support through a user-friendly conversational interface, catering to individual learning styles and needs. The system is open domain, capable of engaging students in 130 languages worldwide, ensuring no student is left behind.

Interview Igniter is an AI-powered platform that provides job seekers with a robust interview simulation to fine-tune their skills, adapt to their learning curve, and get detailed feedback. It offers a comprehensive question bank, including industry-specific questions and actual interview questions asked by leading tech companies like Google, Facebook, Apple, and Amazon. Interview Igniter also provides a coding interview tool for practicing and improving coding skills, with interactive guidance and tailored learning experiences. The platform utilizes Conversation Intelligence tools for analyzing communication in real-time and providing nuanced feedback. Interview Igniter was created by Vidal Graupera, a former engineering manager at LinkedIn and Uber with over 20 years of experience hiring.

Interviews Chat is an AI-powered interview preparation tool that offers real-time suggestions, personalized question preparation, and in-depth feedback to help users ace their interviews. The tool includes a Copilot feature with vision capability for coding challenges and whiteboard tasks. Users can practice answering questions via a video interface, receive tailored interview questions based on their resume and job description, and get instant feedback on their responses. Interviews Chat aims to provide a realistic practice environment to improve interview performance and make a lasting impression.

MindLumen is an AI therapist mobile application designed to provide mental wellbeing support through personalized sessions, educational programs, and self-assessment tests. It offers a safe space for open conversations without judgment, ensuring privacy and security. The app aims to help users manage stress, anxiety, burnout, relationships, shame, and more by offering on-demand support and guidance. MindLumen complements traditional therapy by providing accessible, affordable, and non-judgmental mental health support, making it a practical option for individuals facing barriers to seeking help.

Yodi Relationship Coach App is a mobile application designed to help individuals and couples improve their relationships through personalized coaching, interactive tools, and evidence-based strategies. The app is based on PAIRS, the Practical Application of Intimate Relationship Skills program, developed by leading therapists and educators to help couples, marriages, and families. Yodi aims to enhance the quality of relationships, foster emotional well-being, and promote healthy communication. Users can learn proven communication, conflict resolution, and emotional connection skills, discover immediate benefits and practical tools to improve relationships, and use the app at their own pace with complete privacy at no cost.

Woebot Health is an AI-driven enterprise solution for mental health that aims to increase access to mental health support and improve business outcomes. It offers in-the-moment mental health support through an app, providing interactive conversations, tools for emotional regulation, mood monitoring, and management. Woebot is not generative AI but rules-based, incorporating elements from Cognitive Behavioral Therapy, Interpersonal Psychotherapy, and Dialectical Behavioral Therapy. The platform also includes data analytics to aggregate insights for clinicians and increase visibility beyond traditional care settings.

MediCodio is an AI medical coding assistant that combines automation with medical coders' expertise. It uses advanced technologies such as AI, ML, RPA, and NLP to suggest relevant codes based on patient charts, improving accuracy and speed within revenue cycle management. The tool streamlines the coding process, minimizes claim denials, increases revenue, and reduces coder burnout by relieving the burden on medical coders.

Google Colab Copilot is an AI tool that integrates the GitHub Copilot functionality into Google Colab, allowing users to easily generate code suggestions and improve their coding workflow. By following a simple setup guide, users can start using the tool to enhance their coding experience and boost productivity. With features like code generation, auto-completion, and real-time suggestions, Google Colab Copilot is a valuable tool for developers looking to streamline their coding process.

Chat Blackbox is an AI tool that specializes in AI code generation, code chat, and code search. It provides a platform where users can interact with AI to generate code, discuss code-related topics, and search for specific code snippets. The tool leverages artificial intelligence algorithms to enhance the coding experience and streamline the development process. With Chat Blackbox, users can access a wide range of features to improve their coding skills and efficiency.

Navina AI is a clinician-first AI platform designed to streamline patient care by providing key insights and actionable recommendations to healthcare providers, ACOs, MSOs, and health plans. The platform leverages proprietary AI technology to improve clinical decision-making, reduce administrative burden, and enhance quality management and risk adjustment processes. Navina AI offers efficient chart review, accurate risk adjustment, streamlined quality management, robust analytics, and a user-friendly interface that integrates seamlessly into the clinical workflow.

StudyWithGpt.com is a GPT-powered full-stack learning hub that provides personalized AI tutorials for various tech stacks including Java, PHP, Golang, Python, front-end, back-end, DevOps, and microservices. The AI Full-Stack Mentor offers tailored tutorials based on the user's learning objectives, breaking down knowledge points and providing 24/7 assistance. Users can ask questions, receive tutorial outlines, and get help with tough problems from the AI tutor.

Instructa AI Prompts is an open-source repository dedicated to collecting and sharing AI prompts, best practices, and curated rules for developers. The goal is to help users quickly set up and refine their workflow with ready-to-use prompts. Users can dynamically include prompts in AI-assisted coding tools like Cursor, GitHub Copilot, Zed, Windsurf, and Cline to adhere to project-specific coding standards, best practices, and automation workflows.

CodeGate is a local gateway that enhances the safety of AI coding assistants by ensuring AI-generated recommendations adhere to best practices, safeguarding code integrity, and protecting individual privacy. Developed by Stacklok, CodeGate allows users to confidently leverage AI in their development workflow without compromising security or productivity. It works seamlessly with coding assistants, providing real-time security analysis of AI suggestions. CodeGate is designed with privacy at its core, keeping all data on the user's machine and offering complete control over data.

Claude Coder is an AI-powered coding companion in the form of a VS Code extension that helps users transform ideas into code, convert designs into applications, debug intuitively, accelerate development with automation, and improve coding skills. It aims to bridge the gap between imagination and implementation, making coding accessible and efficient for developers of all skill levels.

MCPHost is a CLI host application that enables Large Language Models (LLMs) to interact with external tools through the Model Context Protocol (MCP). It acts as a host in the MCP client-server architecture, allowing language models to access external tools and data sources, maintain consistent context across interactions, and execute commands safely. The tool supports interactive conversations with Claude 3.5 Sonnet and Ollama models, multiple concurrent MCP servers, dynamic tool discovery and integration, configurable server locations and arguments, and a consistent command interface across model types.

Academic_LLM_Sec_Papers is a curated collection of academic papers related to LLM Security Application. The repository includes papers sorted by conference name and published year, covering topics such as large language models for blockchain security, software engineering, machine learning, and more. Developers and researchers are welcome to contribute additional published papers to the list. The repository also provides information on listed conferences and journals related to security, networking, software engineering, and cryptography. The papers cover a wide range of topics including privacy risks, ethical concerns, vulnerabilities, threat modeling, code analysis, fuzzing, and more.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

OpenRedTeaming is a repository focused on red teaming for generative models, specifically large language models (LLMs). The repository provides a comprehensive survey on potential attacks on GenAI and robust safeguards. It covers attack strategies, evaluation metrics, benchmarks, and defensive approaches. The repository also implements over 30 auto red teaming methods. It includes surveys, taxonomies, attack strategies, and risks related to LLMs. The goal is to understand vulnerabilities and develop defenses against adversarial attacks on large language models.

Repopack is a powerful tool that packs your entire repository into a single, AI-friendly file. It optimizes your codebase for AI comprehension, is simple to use with customizable options, and respects Gitignore files for security. The tool generates a packed file with clear separators and AI-oriented explanations, making it ideal for use with Generative AI tools like Claude or ChatGPT. Repopack offers command line options, configuration settings, and multiple methods for setting ignore patterns to exclude specific files or directories during the packing process. It includes features like comment removal for supported file types and a security check using Secretlint to detect sensitive information in files.

Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. It is designed to format your codebase for easy understanding by AI tools like Large Language Models (LLMs), Claude, ChatGPT, and Gemini. Repomix offers features such as AI optimization, token counting, simplicity in usage, customization options, Git awareness, and security-focused checks using Secretlint. It allows users to pack their entire repository or specific directories/files using glob patterns, and even supports processing remote Git repositories. The tool generates output in plain text, XML, or Markdown formats, with options for including/excluding files, removing comments, and performing security checks. Repomix also provides a global configuration option, custom instructions for AI context, and a security check feature to detect sensitive information in files.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

Mastering GitHub Copilot for AI Paired Programming is a comprehensive course designed to equip you with the skills and knowledge necessary to harness the power of GitHub Copilot, an AI-driven coding assistant. Through a series of engaging lessons, you will learn how to seamlessly integrate GitHub Copilot into your workflow, leveraging its autocompletion, customizable features, and advanced programming techniques. This course is tailored to provide you with a deep understanding of AI-driven algorithms and best practices, enabling you to enhance code quality and accelerate your coding skills. By embracing the transformative power of AI paired programming, you will gain the tools and confidence needed to succeed in today's dynamic software development landscape.

Monacopilot is a powerful and customizable AI auto-completion plugin for the Monaco Editor. It supports multiple AI providers such as Anthropic, OpenAI, Groq, and Google, providing real-time code completions with an efficient caching system. The plugin offers context-aware suggestions, customizable completion behavior, and framework agnostic features. Users can also customize the model support and trigger completions manually. Monacopilot is designed to enhance coding productivity by providing accurate and contextually appropriate completions in daily spoken language.

Refact.ai is an open-source AI coding assistant that boosts developer's productivity. It supports 25+ programming languages and offers features like code completion, AI Toolbox for code explanation and refactoring, integrated in-IDE chat, and self-hosting or cloud version. The Enterprise plan provides enhanced customization, security, fine-tuning, user statistics, efficient inference, priority support, and access to 20+ LLMs for up to 50 engineers per GPU.

Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

The LLM Prompt Tuning Playbook is a comprehensive guide for improving the performance of post-trained Language Models (LLMs) through effective prompting strategies. It covers topics such as pre-training vs. post-training, considerations for prompting, a rudimentary style guide for prompts, and a procedure for iterating on new system instructions. The playbook emphasizes the importance of clear, concise, and explicit instructions to guide LLMs in generating desired outputs. It also highlights the iterative nature of prompt development and the need for systematic evaluation of model responses.

Awesome LLM for APR is a repository dedicated to exploring the capabilities of Large Language Models (LLMs) in Automated Program Repair (APR). It provides a comprehensive collection of research papers, tools, and resources related to using LLMs for various scenarios such as repairing semantic bugs, security vulnerabilities, syntax errors, programming problems, static warnings, self-debugging, type errors, web UI tests, smart contracts, hardware bugs, performance bugs, API misuses, crash bugs, test case repairs, formal proofs, GitHub issues, code reviews, motion planners, human studies, and patch correctness assessments. The repository serves as a valuable reference for researchers and practitioners interested in leveraging LLMs for automated program repair.

An AI that gamifies coding practices for skill improvement and engagement.

GPT security specialist with tailored test scenarios.

Web developer providing constructive code critiques.

Senior Engineer aiding in JavaScript coding and best practices.

Skilled in teaching C++ 98 with clear, beginner-friendly examples.

Get into FAANG. Practice with an AI expert in algorithms, data structures, and system design. Do a mock interview and improve.

Interactive guide for step-by-step secure coding exercises.

I conduct mock system design interviews.

Assists with tech exam prep, adheres to specific rules.

帮助用户学习和掌握编程知识

問題集からバックエンドの技術質問（57+問）をランダムで出題します。回答に対して点数、評価ポイント、改善点を出し、最終的に面接に合格したかどうかを判断します。こちらはサンプルバージョンです。掲載問題数は減らしています。

Guiding you from beginner to expert in Competitive Programming, or simply explain solutions to your problems.

I provide Python interview prep and conduct mock interviews.

This game combines humor and challenge, offering players a laugh-filled journey through the world of cybersecurity and AI.

다양한 파이썬 예제로 여러분에 파이썬 학습을 책임집니다!

Prepares questions for Technical Interviews

Master Class - Teaching and creating code examples.

A GPT dedicated to enhancing psychological resilience through proven exercises, thoughtful advice, and effective coping strategies.

Check your coding skill from uploaded codes.

Advance your Python skills and break through tough coding problems with expert mentoring, blending real-world wisdom and cutting-edge techniques.