This specialization explores the fundamentals, techniques, and applications of prompt engineering in generative AI. It is divided into three distinct courses, guiding learners from the basics to advanced techniques.
In the first course you'll learn the fundamentals of AI and how prompts guide AI models like GPT, DALL-E, and BERT. Through structured exercises, you'll understand how to create effective prompts and apply them across industries, including business, creative writing, and coding.
The second course dives deeper into application-specific prompt engineering. You'll gain hands-on experience with cutting-edge tools like ChatGPT, DALL-E, BERT, and Codex, learning how to tackle advanced tasks in areas such as language learning, image generation, and code creation.
In the final course you'll explore the future of prompt engineering, experimenting with platforms like BigGAN, RunwayML, and DeepFaceLab. You'll explore innovative tools and how they integrate into creative and technical workflows. By the end of this specialization, you'll be equipped to design high-impact prompts for diverse generative AI platforms.
Copyright © 2024 by John Wiley & Sons, Inc. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada.
Used by arrangement with John Wiley & Sons, Inc.
This Specialization is based on the book The Quick Guide to Prompt Engineering, by Wiley and Sons, Ian Khan.
Applied Learning Project
Applied practice activities throughout the courses provide learners with structured opportunities to apply key concepts of prompt engineering in real-world contexts. By working with tools like GPT, DALL-E, BERT, and Codex, learners will tackle challenges such as generating creative content, building code, and refining prompts for language models. These hands-on exercises allow learners to gain practical experience and develop problem-solving skills, culminating in a portfolio that demonstrates their ability to craft effective prompts across various AI platforms.

















