Unlock the full potential of generative AI and become a master of prompt engineering. Dive deeper into how you can use In-context Learning to build better and more reliable prompts. See how Retrieval Augmented Generation (RAG) works and what can go wrong that you can counteract with fact-checkable prompt formats. Overcome your struggles in getting the right output from generative AI models with template-based output formats to achieve precision in your interactions with AI models. Tap into powerful AI capabilities for tasks ranging from social media comment analysis to survey results interpretation and beyond. This course will empower you with the skills needed to build exceptional prompts, using simple techniques, such as preference-driven refinement, and become and expert in leveraging generative AI for productivity and creativity.

What You Will Learn: In-Context Learning: Understand how to provide context within prompts to guide AI models towards more accurate and relevant outputs. Learn techniques to embed contextual information that enhances the model’s understanding and performance. Retrieval Augmented Generation (RAG): Explore how to integrate retrieval systems with generative models to provide more precise and informed responses. This module covers the mechanisms to combine the strengths of both retrieval and generation. Template Pattern and Examples: Master the art of crafting template-based prompts to achieve consistent and desired outputs. Learn how to tell generative AI to fit its output into your format and overcome struggles with getting exactly what you want. Tapping Into AI Capabilities for Everyday Use: Delve into practical applications such as analyzing social media comments, interpreting survey results, and other everyday tasks where generative AI can make a significant impact. Gain hands-on experience with real-world examples. Building Great Prompts: Discover simple methods for constructing effective prompts. Learn how preference-driven refinement can elevate your prompt engineering skills, ensuring that outputs meet your exact needs and preferences.