RoadMap To Learn Prompt Engineering.
📢 Hey everyone! 🌟 I’m excited to share with you the ultimate roadmap for learning and mastering Prompt Engineering. 🚀 Whether you’re a seasoned professional or just starting out, this roadmap will guide you through each and every topic, making it easy to understand and apply Prompt Engineering concepts. 💡 Let’s dive in! 💪
✨ Basic LLM Concepts ✨
- Let’s start by understanding the fundamentals of Language Models (LLMs). 🧠
- Discover what LLMs are and explore their various types. 🤔
- Learn how LLMs are built and gain insights into the underlying processes. 🛠️
- Familiarize yourself with the essential vocabulary used in the world of Prompt Engineering. 📚
🔍 Introduction to Prompting 🔍
- Get introduced to the concept of prompting and its significance in leveraging LLMs effectively. 📝
- Learn the basics of creating prompts and understand their structure and components. 🗒️
- Discover the characteristics of good prompts and how they impact the performance of LLMs. ✅
- Explore techniques such as using delimiters, incorporating structured output, and providing style information within prompts. 📊
🚀 Prompting Techniques 🚀
- Dive into advanced prompting techniques such as Role Prompting, Few Shot Prompting, and Chain of Thought. 🚀
- Uncover the power of the Zero-Shot Chain of Thought and Least to Most Prompting Approaches. 🔑
- Learn about the Dual Prompt Approach and how it can enhance the capabilities of LLMs. 💡
- Discover the art of combining different prompting techniques to achieve even more impressive results. 🌟
💼 Real-World Usage Examples 💼
- Explore real-world applications of Prompt Engineering across various domains. 💼
- Discover how LLMs can be leveraged for tasks such as handling structured data, inferring information, writing emails, providing coding assistance, being a study buddy, and designing chatbots. 💻📧📊📚🤖
🚩 Pitfalls of LLMs 🚩
- Understand the potential pitfalls associated with Language Models. 🚧
- Learn how to address issues related to citing sources, bias, hallucinations, and challenges in mathematical tasks. ⚠️📚
- Explore strategies for prompt hacking, improving reliability, prompt debiasing, and prompt ensembling. 🔒
📈 LLM Self-Evaluation and Calibration 📈
- Discover techniques for evaluating and calibrating the performance of LLMs. 🔄
- Explore methods for assessing the reliability of generated outputs and addressing mathematical challenges. 📐🔄
- Understand LLM settings such as temperature, top P sampling, and other hyperparameters that can impact results. 🌡️📊
🔐 Defensive and Offensive Measures 🔐
- Delve into defensive measures to protect against prompt hacking, prompt leaking, and jailbreaking attempts. 🛡️
- Explore offensive measures to leverage LLMs creatively and optimize their output. ⚔️
📸 Image Prompting 📸
- Unlock the potential of image prompting and learn how to use it effectively with LLMs. 🖼️
- Discover techniques for applying style modifiers, incorporating quality boosters, and utilizing weighted terms. 🌈💪
🔧 Improving Prompt Engineering Skills 🔧
- Gain insights into fixing deformed generations and enhancing the quality of LLM outputs. 🛠️✨
📚 This comprehensive roadmap covers all the essential topics and techniques you need to master Prompt Engineering.
So, let’s embark on this exciting journey together! 🚀💪
Feel free to ask me any questions or share your thoughts in the comments below. Let’s excel in Prompt Engineering and unlock the true potential of Language Models! 🌟💡✨
#PromptEngineering #LLM #LanguageModels #AI #LearningRoadmap
Let's connect: My Linkedin Profile Link :-> https://www.linkedin.com/in/jillani-softtech/
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https://www.kaggle.com/jillanisofttech
