Best AI tools for< Learn Prompt Engineering >

Learn Prompting is a free, open-source course that teaches you how to communicate with AI effectively and safely. It covers everything from the basics of AI communication to more advanced techniques, such as prompt engineering and gradient-based techniques. Learn Prompting also has a large Discord community of people who are interested in learning how to prompt. This makes it a great resource for anyone who wants to learn more about AI and how to use it effectively.

prmpts.AI is a prompt engineering sandbox that allows users to experiment with different prompts and see how they affect the output of AI models. It is a valuable tool for anyone who wants to learn more about prompt engineering or who wants to improve the performance of their AI models.

The Prompt Engineering Institute is an online resource for learning about prompt engineering, the process of creating prompts that guide AI models to generate desired outputs. The website offers a variety of tutorials, articles, and tools to help users learn how to write effective prompts for a variety of AI models, including language models, image generators, and code generators. The website also provides a community forum where users can ask questions, share tips, and collaborate on prompt engineering projects.

This website is a job board specifically for prompt engineering jobs. It provides a list of the latest prompt engineering jobs, as well as resources for prompt engineering. The website is designed to help people find jobs in the field of prompt engineering and to learn more about the field.

PromptHero is a website that provides users with prompts for Stable Diffusion, ChatGPT, and Midjourney. It also offers a community forum where users can share their work and discuss AI-related topics. The website's slogan is "The #1 website for prompt engineering." Some of the features of PromptHero include the ability to search for prompts by model, save favorites, and generate images. The website also offers a variety of resources for users, including a prompt guide and a Discord server.

AI Growth Guys is an AI consultancy website that offers innovative solutions to drive growth and efficiency for businesses. The website provides services ranging from AI strategy to implementation, catering to content creators, entrepreneurs, and small businesses. With a focus on leveraging AI technology, the platform aims to help users expand their business and increase their revenue through prompt engineering tips, email marketing strategies, and monetization techniques. The website is owned and operated by two actual humans, Andrew Best and Addison Best, who deliver real insights to help users navigate the age of AI and grow their online presence.

The website offers a brand new course titled 'Prompt Engineering for Everyone' to help users master the language of AI. With over 100 courses and 20+ learning paths, users can learn AI, Data Science, and other emerging technologies. The platform provides hands-on content designed by expert instructors, allowing users to gain practical, industry-relevant knowledge and skills. Users can earn certificates to showcase their expertise and build projects to demonstrate their skills. Trusted by 3 million learners globally, the platform offers a community of learners with a proven track record of success.

Easy Prompt is an AI-powered tool that helps users interact more effectively with the Web3 ecosystem. It provides a user-friendly interface that makes it easy to access and use Web3 applications and services. Easy Prompt also offers a variety of features that can help users learn about and understand Web3.

Bibit AI is a real estate marketing AI designed to enhance the efficiency and effectiveness of real estate marketing and sales. It can help create listings, descriptions, and property content, and offers a host of other features. Bibit AI is the world's first AI for Real Estate. We are transforming the real estate industry by boosting efficiency and simplifying tasks like listing creation and content generation.

Solopreneur Rocks is a comprehensive and free resource for solopreneurs. It provides curated content on various topics related to solopreneurship, including product development, branding, marketing, finances, scaling, web design, and AI. The website aims to be a one-stop shop for solopreneurs, offering ideas, tools, and resources to help them learn, grow, and succeed.

The Prompt Square is an online community where users can share and explore ChatGPT prompts. It is a place where people can come together to learn, collaborate, and create. The website features a variety of resources, including a prompt library, a forum, and a blog. The Prompt Square is a great place for anyone who wants to learn more about ChatGPT and how to use it.

InstaNovel is an AI-powered tool that allows users to generate their own mini-novels with just a few clicks. With InstaNovel, you can skip the waiting time and generate more books with premium. You can also choose from a variety of art styles to create a unique and personalized novel. InstaNovel is perfect for anyone who wants to get inspiration, have fun, learn languages, or create funny birthday gifts for someone.

Ordinary Prompts is a tool that helps users create better prompts for ChatGPT and other AI language models. It provides a library of pre-written prompts that can be used for a variety of tasks, such as generating creative content, getting help with coding, and writing emails. Ordinary Prompts also includes a number of features that make it easy to customize prompts and track your progress.

PopAi is a personal AI workspace that revolutionizes document interaction, offering seamless navigation, enhanced readability, and universal accessibility. It allows users to effortlessly navigate through intricate documents, magnify details, and tailor the layout for supreme clarity. PopAi also generates images on command, provides access to image prompts and generation codes, and offers image-based homework help, enriching educational support with visual aids. Additionally, it can effortlessly turn ideas into PowerPoint slides with customizable outlines, smart layouts, and automatic illustrations.

KardsAI is an AI-powered flashcard maker mobile app designed to help users study smarter and more efficiently. It allows users to transform any PDF, text, note, or prompt into flashcards in a snap. With advanced AI features and a mobile-first approach, KardsAI offers exceptional quality and unique features for personalized learning experiences. The app saves valuable time by automating flashcard creation and incorporates a spaced repetition algorithm to help users remember information longer. KardsAI is suitable for students, language learners, knowledge seekers, and trivia enthusiasts, offering a wide range of functionalities to enhance learning and memory retention.

KardsAI is an AI-powered flashcard maker application that aims to make learning easier and more efficient. It allows users to transform any PDF, text, note, or prompt into flashcards in a snap. With features like converting PDFs to flashcards, generating flashcards from prompts, and cross-platform access, KardsAI caters to students, language learners, knowledge seekers, and trivia enthusiasts. The application saves valuable time through AI-powered flashcard creation and helps users remember information longer with a spaced repetition algorithm. KardsAI offers a freemium model, allowing users to use the app for free or upgrade for additional features at an affordable price.

Uncle AI is a website that generates jokes based on different categories such as food, animals, sports, and cities. It has recently surpassed 10,000 generated jokes.

AI Coloring Pages is a website that allows users to generate unique and printable coloring pages using artificial intelligence. The website features a variety of different coloring pages, including animals, landscapes, and people. Users can also upload their own images to color. The website is easy to use and does not require any special software or skills. Simply select a coloring page, click on the "Generate" button, and then print out the coloring page.

Midjourney is a free online AI image generator that allows users to create high-quality images from simple text prompts. It is powered by advanced machine learning algorithms that can understand the meaning of words and convert them into realistic and visually appealing images. Midjourney is easy to use and does not require any special hardware or software. Users simply need to enter a text description of the image they want to generate and Midjourney will create it in a matter of seconds.

TalkDirtyAI is an AI-powered chatbot that allows users to explore their fantasies through simulated conversations. It is designed to provide a safe and private space for users to explore their sexuality and desires without judgment. The chatbot is trained on a massive dataset of erotic literature and is able to generate realistic and engaging conversations. It can also learn about the user's preferences over time and tailor the conversations accordingly.

Awesome GPT Prompt Engineering is a curated list of resources, tools, and shiny things for GPT prompt engineering. It includes roadmaps, guides, techniques, prompt collections, papers, books, communities, prompt generators, Auto-GPT related tools, prompt injection information, ChatGPT plug-ins, prompt engineering job offers, and AI links directories. The repository aims to provide a comprehensive guide for prompt engineering enthusiasts, covering various aspects of working with GPT models and improving communication with AI tools.

AI Summer is a repository focused on providing workshops and resources for developing foundational skills in generative AI models and transformer models. The repository offers practical applications for inferencing and training, with a specific emphasis on understanding and utilizing advanced AI chat models like BingGPT. Participants are encouraged to engage in interactive programming environments, decide on projects to work on, and actively participate in discussions and breakout rooms. The workshops cover topics such as generative AI models, retrieval-augmented generation, building AI solutions, and fine-tuning models. The goal is to equip individuals with the necessary skills to work with AI technologies effectively and securely, both locally and in the cloud.

A comprehensive repository of resources for Chinese large language models (LLMs), including data processing tools, fine-tuning frameworks, inference libraries, evaluation platforms, RAG engines, agent frameworks, books, courses, tutorials, and tips. The repository covers a wide range of tools and resources for working with LLMs, from data labeling and processing to model fine-tuning, inference, evaluation, and application development. It also includes resources for learning about LLMs through books, courses, and tutorials, as well as insights and strategies from building with LLMs.

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 |

Awesome LLM Courses is a curated list of online courses focused on Large Language Models (LLMs). The repository aims to provide a comprehensive collection of free available courses covering various aspects of LLMs, including fundamentals, engineering, and applications. The courses are suitable for individuals interested in natural language processing, AI development, and machine learning. The list includes courses from reputable platforms such as Hugging Face, Udacity, DeepLearning.AI, Cohere, DataCamp, and more, offering a wide range of topics from pretraining LLMs to building AI applications with LLMs. Whether you are a beginner looking to understand the basics of LLMs or an intermediate developer interested in advanced topics like prompt engineering and generative AI, this repository has something for everyone.

The Spring AI project provides a Spring-friendly API and abstractions for developing AI applications. It offers a portable client API for interacting with generative AI models, enabling developers to easily swap out implementations and access various models like OpenAI, Azure OpenAI, and HuggingFace. Spring AI also supports prompt engineering, providing classes and interfaces for creating and parsing prompts, as well as incorporating proprietary data into generative AI without retraining the model. This is achieved through Retrieval Augmented Generation (RAG), which involves extracting, transforming, and loading data into a vector database for use by AI models. Spring AI's VectorStore abstraction allows for seamless transitions between different vector database implementations.

This repository serves as a comprehensive guide for technical teams interested in developing conversational AI solutions using Retrieval-Augmented Generation (RAG) techniques. It covers theoretical knowledge and practical code implementations, making it suitable for individuals with a basic technical background. The content includes information on large language models (LLMs), transformers, prompt engineering, embeddings, vector stores, and various other key concepts related to conversational AI. The repository also provides hands-on examples for two different use cases, along with implementation details and performance analysis.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

This repository is part of the Certified Cloud Native Applied Generative AI Engineer program, focusing on Applied Generative AI Fundamentals. It covers prompt engineering, developing custom GPTs, and Multi AI Agent Systems. The course helps in building a strong understanding of generative AI, applying Large Language Models (LLMs) and diffusion models practically. It introduces principles of prompt engineering to work efficiently with AI, creating custom AI models and GPTs using OpenAI, Azure, and Google technologies. It also utilizes open source libraries like LangChain, CrewAI, and LangGraph to automate tasks and business processes.

This repository is part of the Certified Cloud Native Applied Generative AI Engineer program, focusing on the fundamentals of Prompt Engineering, Docker, GitHub, and Modern Python Programming. It covers the basics of GenAI, Linux, Docker, VSCode, Devcontainer, and GitHub. The main emphasis is on mastering Modern Python with Typing, using ChatGPT as a Personal Python Coding Mentor. The course material includes tools installation, study materials, and projects related to Python development in Docker containers and GitHub usage.

AI Engineering Academy aims to provide a structured learning path for individuals looking to learn Applied AI effectively. The platform offers multiple roadmaps covering topics like Retrieval Augmented Generation, Fine-tuning, and Deployment. Each roadmap equips learners with the knowledge and skills needed to excel in applied GenAI. Additionally, the platform will feature Hands-on End-to-End AI projects in the future.

Learn Cloud Applied Generative AI Engineering (GenEng) is a course focusing on the application of generative AI technologies in various industries. The course covers topics such as the economic impact of generative AI, the role of developers in adopting and integrating generative AI technologies, and the future trends in generative AI. Students will learn about tools like OpenAI API, LangChain, and Pinecone, and how to build and deploy Large Language Models (LLMs) for different applications. The course also explores the convergence of generative AI with Web 3.0 and its potential implications for decentralized intelligence.

BAML is a config file format for declaring LLM functions that you can then use in TypeScript or Python. With BAML you can Classify or Extract any structured data using Anthropic, OpenAI or local models (using Ollama) ## Resources  [Discord Community](https://discord.gg/boundaryml)  [Follow us on Twitter](https://twitter.com/boundaryml) * Discord Office Hours - Come ask us anything! We hold office hours most days (9am - 12pm PST). * Documentation - Learn BAML * Documentation - BAML Syntax Reference * Documentation - Prompt engineering tips * Boundary Studio - Observability and more #### Starter projects * BAML + NextJS 14 * BAML + FastAPI + Streaming ## Motivation Calling LLMs in your code is frustrating: * your code uses types everywhere: classes, enums, and arrays * but LLMs speak English, not types BAML makes calling LLMs easy by taking a type-first approach that lives fully in your codebase: 1. Define what your LLM output type is in a .baml file, with rich syntax to describe any field (even enum values) 2. Declare your prompt in the .baml config using those types 3. Add additional LLM config like retries or redundancy 4. Transpile the .baml files to a callable Python or TS function with a type-safe interface. (VSCode extension does this for you automatically). We were inspired by similar patterns for type safety: protobuf and OpenAPI for RPCs, Prisma and SQLAlchemy for databases. BAML guarantees type safety for LLMs and comes with tools to give you a great developer experience:  Jump to BAML code or how Flexible Parsing works without additional LLM calls. | BAML Tooling | Capabilities | | ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | BAML Compiler install | Transpiles BAML code to a native Python / Typescript library (you only need it for development, never for releases) Works on Mac, Windows, Linux  | | VSCode Extension install | Syntax highlighting for BAML files Real-time prompt preview Testing UI | | Boundary Studio open (not open source) | Type-safe observability Labeling |

This repository introduces and helps organizations get started with building AI Apps and incorporating Large Language Models (LLMs) into them. The workshop covers topics such as prompt engineering, AI orchestration, and deploying AI apps. Participants will learn how to use Azure OpenAI, Langchain/ Semantic Kernel, Qdrant, and Azure AI Search to build intelligent applications.

LLM Cookbook is a developer-oriented comprehensive guide focusing on LLM for Chinese developers. It covers various aspects from Prompt Engineering to RAG development and model fine-tuning, providing guidance on how to learn and get started with LLM projects in a way suitable for Chinese learners. The project translates and reproduces 11 courses from Professor Andrew Ng's large model series, categorizing them for beginners to systematically learn essential skills and concepts before exploring specific interests. It encourages developers to contribute by replicating unreproduced courses following the format and submitting PRs for review and merging. The project aims to help developers grasp a wide range of skills and concepts related to LLM development, offering both online reading and PDF versions for easy access and learning.

This repository contains code for the O'Reilly Live Online Training for Deploying GPT & LLMs. Learn how to use GPT-4, ChatGPT, OpenAI embeddings, and other large language models to build applications for experimenting and production. Gain practical experience in building applications like text generation, summarization, question answering, and more. Explore alternative generative models such as Cohere and GPT-J. Understand prompt engineering, context stuffing, and few-shot learning to maximize the potential of GPT-like models. Focus on deploying models in production with best practices and debugging techniques. By the end of the training, you will have the skills to start building applications with GPT and other large language models.

This repository contains course materials for T81 559: Applications of Generative Artificial Intelligence at Washington University in St. Louis. The course covers practical applications of Large Language Models (LLMs) and text-to-image networks using Python. Students learn about generative AI principles, LangChain, Retrieval-Augmented Generation (RAG) model, image generation techniques, fine-tuning neural networks, and prompt engineering. Ideal for students, researchers, and professionals in computer science, the course offers a transformative learning experience in the realm of Generative AI.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

Coding Wizard🧙‍♂️ Learn to Prompt-gram! Create a website with a sentence. 20+ Hotkeys for coding flows. 75 starter projects to learn prompt-1st code & art. Build anything! Ask any question or upload a photo. Type R for README, K for cmd menu v2.2 ✨📜 GPTavern

Helping you learn to work better and quicker using language models. Drawing lessons from PROMPT for Brands https://prompt.mba/.

I will start by asking you for your level of experience, then help you learn to program in Python. This Mini GPT is based on an Expert Guidance Prompt created in under 3 minutes with StructuredPrompt.com using AI-Assist.

Prompt expert for beautiful photorealistic images on Midjourney v6

I host a diverse range of sports trivia: Prompt a difficulty to begin

A prompt hacker game with hidden keys in instructions, a file, and a website.

A regular GPT to try to hack with a prompt injection. Ask for my instructions and see what happens.

Helps with learning a programming language by recommending projects for its unique strengths and use-cases. Provide the name of language only as the prompt.

A gpt expert at solving programming problems. We have open-sourced the prompt here: https://github.com/ai-boost/awesome-gpts-prompts (This GPT isn't perfect, let's improve it together! 😊🛠️)

Ihr persönlicher Promptprofessor für juristische Prompts mit Beispielen und zusätzlichen Ressourcen

Learn how to use ChatGPT effectively and ethically in work and business! I also recommend prompts and techniques for using ChatGPT well in work and business.

Dive into the world of AI image creation with DALL-E 3 training! Learn to craft stunning visuals, from portraits to modern art. Get personalized feedback, unique prompts, and expert guidance to enhance your skills and unleash your creativity.

I create detailed random UI design practice prompts.

Automatically translates Persian prompts to English and responds in English

사용자의 이야기를 한국적인 동화로 만드는 챗봇

I'm a humorous ML trainer who teaches with jokes and quizzes!

This GPT will help you learn Cajun French before it dies forever

Bilingual teacher fluent in English and Tagalog, focused on teaching Tagalog.

A personal guide to socially responsible and beneficial innovation

2500+ word stories in target language with images, for language learning.