AWS Generative AI Prompt Engineering and Model Selection Workshop

Master the art of selecting the right Large Language Models (LLMs) and creating optimized prompts for your healthcare applications with Reveal HealthTech’s AWS Generative AI Model Selection and Prompt Engineering Workshop.

In this hands-on session, you will learn how to choose the most suitable models from Amazon Bedrock, including third-party models like Anthropic Claude, AI21 Jurassic, and Cohere Command, and how to craft effective prompts to maximize the performance of these models.

This workshop is designed specifically for healthcare providers, payers , and life sciences companies who are looking to integrate Generative AI into their processes, enabling them to develop intelligent applications that improve operational efficiency and enhance patient care.

**Workshop Plan and Execution **

The workshop will cover the following core topics:

Introduction to Generative AI and Model Selection (60 minutes)

• Understand the different LLMs available through Amazon Bedrock, including first-party models like Amazon Titan and third-party models such as Anthropic Claude, AI21 Jurassic, and Cohere Command.
• Learn the best practices for evaluating and selecting the appropriate model based on your specific use case, considering factors such as accuracy, performance, and domain-specific requirements in healthcare.

Output: An understanding of the strengths and weaknesses of each model and how they apply to various healthcare tasks.

Prompt Engineering Fundamentals (60 minutes)

• Learn the basics of prompt engineering, including the structure of prompts (instructions, context, input, output) and how to design clear, concise, and effective prompts tailored to your use case.
• Explore general tips and tricks, such as using context, providing examples, and experimenting with different prompt structures to achieve the best results.

Output: Hands-on practice designing prompts for healthcare-specific tasks, such as summarization of clinical notes, generating patient reports, and answering medical questions.

Advanced Prompt Engineering Techniques (90 minutes)

• Dive deeper into advanced techniques like Zero-Shot, Few-Shot, Chain-of-Thought (CoT), and ReAct prompting to handle complex healthcare queries and tasks.
• Learn how to utilize model parameters, such as temperature, top_p, and stop sequences, to control the output of the models and ensure that they meet the desired criteria.

Output: Proficiency in applying advanced prompt engineering techniques to refine the model’s behaviour and improve response quality for healthcare-specific applications.

Workshop Wrap-Up and Action Plan (60 minutes)

• Recap the key takeaways from the workshop, including best practices for model selection and prompt engineering.
• Collaborate with our AWS experts to create a custom action plan for integrating generative AI solutions into your healthcare systems.

Output: A detailed action plan that outlines the next steps for applying model selection and prompt engineering strategies within your organization.