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OpenAI ChatGPT: Prompt Engineering Best Practices

Struggling to get consistent results from ChatGPT? This course will teach you how to craft effective, reusable prompts and improve output quality using templates, chain-of-thought prompting, and response analysis.

Beginner
52m
(7)

Created by Amber Israelsen

Last Updated Jun 24, 2025

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  • Course

OpenAI ChatGPT: Prompt Engineering Best Practices

Struggling to get consistent results from ChatGPT? This course will teach you how to craft effective, reusable prompts and improve output quality using templates, chain-of-thought prompting, and response analysis.

Beginner
52m
(7)

Created by Amber Israelsen

Last Updated Jun 24, 2025

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What you'll learn

Getting inconsistent or low-quality results from ChatGPT can be frustrating and time-consuming, especially when you're repeating the same tasks. In this course, OpenAI ChatGPT: Prompt Engineering Best Practices, you’ll learn to craft clear, reusable prompts that consistently deliver high-quality output. First, you’ll explore how to build flexible prompt templates for repeatable tasks like content creation, code generation, or brainstorming. Next, you’ll discover how to guide the model with scaffolding techniques such as chain-of-thought prompting and few-shot examples. Finally, you’ll learn how to evaluate and refine responses using qualitative metrics and prompt iteration. When you’re finished with this course, you’ll have the skills and knowledge of prompt engineering needed to work more efficiently and get better results from ChatGPT.

OpenAI ChatGPT: Prompt Engineering Best Practices
Beginner
52m
(7)
Table of contents

About the author
Amber Israelsen - Pluralsight course - OpenAI ChatGPT: Prompt Engineering Best Practices
Amber Israelsen
54 courses 4.7 author rating 5760 ratings

Amber has been a software developer and technical trainer since the early 2000s. She holds certifications for AWS and a variety of Microsoft technologies. She also focuses on user experience and professional skills training, bridging the gap between techies and non-techies.

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