As generative AI (GenAI) continues to reshape the workplace and redefine job roles, the ability to use it effectively is becoming a must-have skill. Prompt engineering is the key to effectively guiding GenAI models and controlling their output to produce desired results.



Generative AI: Prompt Engineering Basics
This course is part of multiple programs.


Instructors: Antonio Cangiano
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(5,306 reviews)
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What you'll learn
Explain the concept, relevance, and best practices of prompt engineering to guide generative AI models in producing meaningful, accurate outputs.
Apply prompt engineering techniques to text prompts, improving the reliability and quality of large language models.
Practice prompt engineering techniques and approaches, including interview pattern, chain-of-thought, tree-of-thought, to improve prompt outcomes.
Explore commonly used tools for prompt engineering to aid with prompt engineering.
Skills you'll gain
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There are 3 modules in this course
In this module, you will learn the key elements of a prompt and how to write them effectively using different formats such as questions, statements, and instructions. You will also explore the concept of prompt engineering and its importance in guiding generative AI models to produce relevant and accurate responses. The module also introduces best practices for prompt creation and provides an overview of commonly used prompt engineering tools. Through hands-on labs, you will practice designing clear, concise, and context-aware prompts, starting with naive approaches and progressing to more refined methods like persona pattern. Additionally, expert insights will help you understand real-world applications and the evolving role of prompt engineering in generative AI.
What's included
7 videos4 readings2 assignments3 app items1 discussion prompt
In this module, you will explore a variety of prompt engineering techniques and approaches that enhance the effectiveness of generative AI models. You will learn how to apply interview pattern, chain of thought (CoT), and tree of thought (ToT) methods/approaches to improve the specificity, coherence, and reasoning capabilities of AI responses. In addition, you will be introduced to emerging strategies like multimodal prompting, which combines inputs across text, images, and other formats to enrich the context and accuracy of model outputs. You'll also learn about the playoff method, which involves generating multiple candidate outputs and selecting or refining the best through iterative comparison. Through hands-on labs, you’ll apply these approaches to create specific, coherent, and diverse prompts for generative AI. Finally, you will gain insights from experts on how to choose the most suitable prompting strategy based on your objective.
What's included
5 videos1 reading2 assignments4 app items1 discussion prompt3 plugins
This module includes a graded quiz to assess and reinforce your understanding of the concepts covered in the course. It also features a glossary to help you better understand generative AI-related terms. Additionally, the module includes a final project, which provides an opportunity to gain hands-on experience on the concepts covered in the course. The module also includes optional content. This content includes the techniques for writing effective prompts for image generation.
What's included
2 videos3 readings1 assignment2 app items1 discussion prompt1 plugin
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Reviewed on Feb 2, 2025
Great content! Especially the lab environment provided by IBM Watsonx is extremely useful. Looking forward to an advanced course in this series.
Reviewed on Jul 19, 2025
this course is vey usefull to get into a prompt engineering . it is usefull for every one who need to move with AI to improve there domain
Reviewed on Aug 3, 2024
The course was so useful and informative. You can learn a lot about how to use the right prompts when using AI in order to get the ideal outcome.
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