Guide to Prompt Engineering

CodeAhoy

Comprehensive course on prompt engineering for AI applications like ChatGPT. Covers fundamentals, advanced techniques, and practical strategies to master the art of effective prompting.

Technical TutorialsArtificial IntelligenceNatural Language Processing

Introduction

Guide to Prompt Engineering by CodeAhoy is a comprehensive course that covers the fundamentals and advanced techniques of prompt engineering. It explores the art of crafting effective prompts for various AI applications, including ChatGPT.

Highlights

Covers the introduction to prompting and its importance
Provides a deep dive into basic and advanced prompting techniques
Explores prompt applications across different domains
Delves into ChatGPT-specific prompt engineering strategies
Addresses adversarial prompting and reliability considerations
Includes a wide range of miscellaneous prompt engineering topics

Recommendation

This course is highly recommended for anyone interested in leveraging the power of AI and language models, including developers, data scientists, content creators, and anyone looking to enhance their prompt engineering skills. It offers a comprehensive and practical approach to mastering the art of prompt engineering.

GetVM 是如何工作的？

从浏览器侧边栏中学习

从浏览器侧边栏中访问

从浏览器侧边栏中访问

简单安装浏览器扩展并点击侧边栏中启动 GetVM。

选择你的环境

选择你的环境

从我们的环境库中选择你的操作系统、IDE 或应用，并立即启动。

边学边做

边学边做

在教程或视频的侧边栏中，在 VM 中实践你的新技能。保存你的工作，以便在将来继续学习。

探索相似的教程

DALL·E 2 Prompt Book | AI-Powered Image Generation, Creative Writing 6

Technical TutorialsArtificial Intelligence

Explore the innovative AI technology of DALL·E 2 that generates realistic images from textual descriptions, offering insights into creative writing and visual artistry.

Prompt Engineering Guide | Comprehensive Resource for Engineering, Programming & Development 8

Technical TutorialsArtificial Intelligence

Explore the Prompt Engineering Guide by DAIR.AI, a comprehensive resource covering prompt engineering, large language models, and practical guidance for building effective applications.

Text Processing in Python 16

Technical TutorialsNatural Language ProcessingPython

Comprehensive guide to working with text data in Python, covering string manipulation, regular expressions, text parsing, and natural language processing.

Unix for Poets | Text Analysis & Poetry 25

Technical TutorialsNatural Language ProcessingUnix

Learn Unix tools and techniques for text analysis and poetry. Explore dictionaries, corpora, and more to unlock the power of text data.

Introduction to TensorFlow for AI, Machine Learning & Deep Learning 6

Video CoursesArtificial IntelligenceNeural NetworksTensorFlow

Gain hands-on experience in building neural networks, training them for computer vision, and understanding the use of convolutions to improve model performance.

MIT's Artificial Intelligence Course | Machine Learning, Computer Science 6

Video CoursesArtificial IntelligenceComputer ScienceMachine Learning

Comprehensive introduction to fundamental AI concepts, including knowledge representation, problem solving, and learning. Develop intelligent systems and explore the role of AI in understanding human intelligence.

Deep Learning for Natural Language Processing | University of Oxford 18

University CoursesDeep LearningMachine LearningNatural Language Processing

Dive into the latest advancements in deep learning for NLP, including text analysis, speech recognition, language translation, and more. Gain a solid theoretical foundation and practical experience.

Deep Learning for Natural Language Processing | Stanford University 6

University CoursesDeep LearningMachine LearningNatural Language Processing

Dive deep into cutting-edge research in deep learning for natural language processing (NLP). Implement, train, and invent your own neural network models for a variety of NLP tasks.

Artificial Intelligence | Introduction to AI - UC Berkeley 13

University CoursesArtificial IntelligenceMachine Learning

Explore the foundations of intelligent computer systems with this comprehensive AI course from UC Berkeley. Build autonomous agents, learn inference techniques, and master machine learning algorithms.