Prompt Refinement: A Data Analyst's Secret Weapon

This session, “Prompt Refinement: A Data Analyst’s Secret Weapon,” will delve into cutting-edge techniques in prompt optimization and reveal how these skills can elevate your data analysis workflows—all from the comfort of your own space!

Whether you’re a data analyst, a student, or simply curious about harnessing Gen AI in your workflow, this workshop will provide valuable tools and insights. Don’t miss out on this opportunity to level up your data analysis skills!

Workshop Highlights:

• Prompt Optimization Techniques – Master ways to craft effective prompts that yield precise results in data analytics.
• Gen AI in Data Preparation – Discover how advanced data cleaning and feature engineering can be achieved using Generative AI tools.
• Inside the LLM Black Box – Gain insight into how Large Language Models (LLMs) learn through one-shot, zero-shot, and few-shot learning techniques.
• Structured Prompt Frameworks – Learn practical frameworks like RACE (Reflect, Apply, Conclude, Evaluate) and PARE (Plan, Act, Review, Enhance) to structure and refine your prompts for consistent success.

Sarwat Zabeen is a Data Scientist and researcher with a strong focus on AI safety, specializing in Reinforcement Learning from Human Feedback (RLHF). Currently pursuing a PhD in Data Science at Harrisburg University of Science and Technology, Sarwat’s research addresses the critical gap in ensuring that RLHF can be implemented safely without compromising the helpfulness of AI models. With a background in machine learning, data analysis, and model optimization, Sarwat is dedicated to advancing the field of AI by developing innovative approaches that balance safety and functionality in AI systems. Passionate about fostering collaboration and driving impactful research, Sarwat is committed to bridging theoretical and practical aspects of AI development.