Summary
Full Transcript
AWS Certified AI Practitioner Exam — Domain 3: Applications of Foundation Models Welcome to Video 8 of our AWS Certified AI Practitioner series! In this video, we dive deep into prompt engineering — a critical skill for working effectively with generative AI models. Whether you're building AI-powered applications or preparing for the AWS AI certification, mastering prompt engineering will help you get better, safer, and more consistent results. 📚 In this video, you will learn: ✅ What is prompt engineering: context, instruction, negative prompts, and latent space 🧩 Techniques: chain-of-thought, zero-shot, single-shot, few-shot, and prompt templates 🎯 Benefits & best practices: response quality, experimentation, guardrails, specificity ⚠️ Risks & limitations: exposure, poisoning, hijacking, jailbreaking 💡 Key Takeaways: Learn how to design effective prompts and avoid common pitfalls 📺 Watch Next: Video 9 will cover Training and Fine-Tuning Foundation Models — including pre-training, instruction tuning, transfer learning, and RLHF. 🔔 Subscribe to stay updated with the full guided series and ace your AWS Certified AI Practitioner exam! 👍 Like, Share, and Comment if this video helped you understand prompt engineering better! #AWS #AIPractitioner #PromptEngineering #GenerativeAI #AWSCertification #MachineLearning #FoundationModels #CLFAI03 #CloudComputing
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