Courses |

Artificial intelligence

Introduction to large language models

In this course, participants are introduced to the foundational concepts, tools, and ethical considerations of large language models. Designed specifically for nonprofit professionals, this course explores how LLMs work, how they differ from other generative AI tools, and how to integrate them responsibly into nonprofit workflows. Through real-world case studies, hands-on prompting techniques, and best practice guidance, learners will gain practical skills for using AI tools to boost productivity, enhance communication, and maximize mission-driven impact.

Complex concepts will be broken down in a digestible way as we explore LLMs like OpenAI’s ChatGPT and Microsoft’s Copilot, and briefly explore related tools. You’ll also get a technical history overview that touches on both development and impact.

You’ll learn practical tips and methods for using generative AI in your day-to-day work, such as improving communication with stakeholders and supporters to strengthen engagement. One of the most valuable takeaways is the focus on ethical implications and considerations related to the use of LLMs. Paired with fun and engaging activities you can try with friends and co-workers, this course is designed to be informative, approachable, and directly useful.

Learning objectives

Learn LLM fundamentals

Understand the core concepts behind LLMs and how they differ from other generative AI models.

Identify meaningful use cases

Discover practical nonprofit applications for LLMs and evaluate which tools are best suited to different needs.

Navigate challenges

Recognize ethical considerations and potential challenges when implementing LLMs in nonprofit settings.

Curriculum outline

• Understand the basics
• How LLMs actually work
• Real-world applications for nonprofits
• Prompt like a pro
• Ethics, challenges, and best practices
• Continue your AI journey

Anticipated time to complete

NTEN courses typically require about 60 minutes of video content to complete, while optional content varies by course.