Virtual Medical Academy

Overview

This lecture introduces participants to the foundations of Generative Artificial Intelligence, covering key AI concepts including Machine Learning, Deep Learning, NLP, and Computer Vision. It explores how Generative AI works through transformer-based models, its types (LLMs, Diffusion Models, GANs, VAEs), and the critical skill of Prompt Engineering — including techniques such as Zero-Shot, Few-Shot, Chain-of-Thought, Step-Back, Self-Refinement, Tree-of-Thoughts, and more. Participants will learn how to craft effective prompts to maximize AI output quality in real-world professional scenarios.

This Activity for

All Target Audience, Can be benefit From This Activity.

What I will learn?

1. Distinguish between AI, Machine Learning, Deep Learning, NLP, and Generative AI to accurately select the appropriate technology for specific use cases in their professional practice.
2. Apply at least 5 prompt engineering techniques (e.g., Zero-Shot, Few-Shot, Chain-of-Thought, Step-Back, Self-Refinement) to generate higher-quality, context-appropriate AI outputs in daily tasks.
3. Configure LLM parameters such as temperature and output length to control and optimize model responses for different professional scenarios.
4. Evaluate AI-generated content critically to identify hallucinations, biases, and privacy risks, and implement responsible AI usage practices in their work environment.
5. Design structured prompts using System, Contextual, and Role prompting frameworks to solve real-world problems such as marketing campaigns, data analysis, or content generation.