Data Science Horizons：2024掌握生成式AI与提示工程：数据科学家的实用指南（英文版）（42页）.pdf

1、Mastering Generative AIand Prompt Engineering:A Practical Guide for Data ScientistsAs the AI-driven economy continues to evolve and expand,the roleof prompt engineering will become increasingly significant andtransformative across diverse sectors and domains.ContentsIntroductionChapter 1:Understandi

2、ng Generative AI1.1.Evolution of AI:From rule-based to generative models1.2.Key generative AI models:RNNs,LSTMs,GPT,and more1.3.Popular use cases for generative AIChapter 2:Introduction to Prompt Engineering2.1.What is prompt engineering and why it matters2.2.Prompt types:explicit,implicit,and creat

3、ive prompts2.3.The role of prompts in guiding AI modelsChapter 3:Designing E?ective Prompts3.1.Understanding your AI model:capabilities and limitations3.2.Crafting clear and concise prompts3.3.Using tokens,temperature,and other parameters3.4.Iterative prompt design:testing and refiningChapter 4:Adva

4、nced Prompt Engineering Techniques4.1.Conditional prompts for context-sensitive AI4.2.Multi-step prompts for complex tasks4.3.Leveraging transfer learning for prompt engineeringChapter 5:Ethical Considerations in Generative AI and Prompt Engineering5.1.Addressing AI biases and fairness5.2.Ensuring t

5、ransparency and explainability5.3.Data privacy and security concernsChapter 6:Real-world Applications and Case Studies6.1.Content generation and creative writing6.2.Data analysis and visualization6.3.Chatbots and conversational AI6.4.Anomaly detection and pattern recognitionConclusionAppendicesA.Rec

6、ommended books,articles,and blogsB:Online communities and forums for discussions and collaboration1IntroductionThe field of artificial intelligence(AI)has come a long way since its inception,with generativeAI and prompt engineering playing crucial roles in its advancement.As data scientists,itsessen