1  Introduction

I generated (not in the AI sense!) these notes over the summer of 2025 in response to an increasing need from instructors and students to obtain some guidance on navigating the Artificial Intelligence (AI) landscape in higher education.

Here, I intend to share thoughts, concerns, and references coming from my experiences in the University of California AI Community of Practice, the University of California Santa Cruz AI Council, conversations with several faculty colleagues at different institutions, students, and current literature regarding the technical and the implementation side of AI.

This course is intended to provide practical guidance and technical considerations on using LLMs in higher education teaching and learning. Large Language Models, or LLMs for short, are a type of Generative Artificial Intelligence (GenAI), which in turns is a type of Artificial Intelligence (AI). Many use these terms interchangeably when referring to LLMs, especially in educational settings. I will focus on LLMs, and will use this terminology, in order to be accurate and to center the discussion around text generation. Similar discussions can be held around image or video generation, as well as other types of AI.

Whether you are a college student or professor, this course will help you explore effective ways to use LLMs in your daily activities. Here, we will discuss writing and coding as one of the most evident use cases, while also reflecting on effective ways to use LLMs to enhance our capacity to teach and learn.

This course includes typical use cases, ethical considerations, environmental concerns, privacy and data aspects, -some- technical elements, and general concepts involved in LLMs.

AI models are rapidly evolving and so are their use cases. This course will be regularly updated in order to include current features and applications.