This presentation explores how Generative AI, particularly Large Language Models (LLMs), can empower engineers with deeper data understanding. We'll delve into creating complex charts using Python and demonstrate how LLMs can analyze these visualizations, identify trends, and suggest actionable insights. Learn how to effectively utilize LLMs through prompt engineering with natural language and discover how this technology can save you valuable time and effort.

Agenda:

1. Introduction to LLMs and their Role in Data Analysis and Training

- What are LLMs, and how do they work?

- LLMs in the context of data analysis and visualization.

2. Prompt Engineering - Guiding the LLM

- Crafting effective prompts for chart analysis.

- Providing context within the prompt (chart type, data).

3. Tokens - The Building Blocks

- Understanding the concept of tokens in LLMs.

- How token limits impact prompt design and model performance.

4. Let AI Help with Data Insights - Real Use Case

- Creating complex charts using Python libraries.

- Write Prompts for Chart Analysis

- Utilizing an LLM to analyze the generated charts.

- Demonstrating how LLMs can identify trends, anomalies, and potential areas for improvement.

6. Live Demo - Create complex charts using python and ask AI to help you with the analysis

- Live coding demonstration of creating a complex chart and using an LLM to analyze it.