
Discover prompt engineering and learn how to create good prompts with guidance from Priya Shastri, a software engineer with 17 years of experience.
Explore how AI makes human-like decisions from narrow to super, and how prompt engineering techniques connect to natural language processing, computer vision, and autonomous cars.
Explore the types of prompts in prompt engineering, including few-shot, zero-shot, and chain-of-thought prompts, plus task specification, contextual guidance, bias mitigation, framing, and domain-expertise Q&A, with examples using ChatGPT.
In this course, you will learn the three important aspects of prompt engineering - data, context and verb. Prompt Engineering is gaining importance since AI tools/applications require good context setting. Why context setting?
Artificial Intelligence (AI) applications are computer systems that do not have memory of previous tasks, they need a context unlike humans who can connect the dots and provide the suitable response. The AI software and tools are performing multiple functionalities in order to simulate a human- like response.
If the AI software is not provided with the context and the sample data the response will not be appropriate for the users. For e.g. When you provide a prompt to chat GPT "Please write me a story on summer". This prompt has the verb "write", context "summer" and the sample response "story" so elongated text. So that provides a complete picture to chatGPT.
Similarly when you provide the prompt "Give me a summary of medals for Olympics 2024 in table format" This prompt will provide the output accurately.
One must know what one wants as response in order to elicit the correct response from AI systems. This course will teach you that information. Good luck on learning Prompt Engineering (PE)!