The following computer science courses have GenAI integrated in the course learning objectives.  Each course includes early integration of generative AI to ensure students gain experience with these tools from the start of their college education and learn to use them ethically and responsibly.  The courses have been developed and piloted by faculty across the United States.

These reference courses are meant to provide a starting point for faculty who wish to integrate GenAI into their courses.  Each course includes available lecture slides and course projects for faculty.  Faculty are encouraged to use their expertise to modify these materials to best serve their students.

List of Courses

Introduction to Programming in Python with GitHub Copilot

This 10-week course teaches students how to write software with GitHub Copilot—including learning both Python fundamentals as well as how to interact with an AI assistant.  Students learn how to read, write, test, and debug Python programs while also understanding how to leverage AI tools to create software that is meaningful to them.  Students learn these concepts in the context of data science, image processing, and game design.  No prior programming experience is required.  View course

Introduction to Computer Science with GenAI

This 15-week course introduces students to the fundamentals of programming and computer science using Python. Through hands-on projects and guided practice, students learn core concepts such as conditionals, loops, functions, data structures, and working with files and APIs. Along the way, students explore how to use generative AI tools to support problem-solving, debugging, and code generation, while also developing skills to evaluate AI output and prompt effectively.  No prior programming experience is required. View course

Object-Oriented Programming and Data Structures with GenAI

This course teaches students object-oriented programming (inheritance, interfaces) as well as basic data structures including stacks, queues, trees, and graphs.  Students also learn best practices for using an AI assistant, including designing effective prompts and how to evaluate GenAI output.   Prior programming experience (variables, loops, conditionals, functions) in Python is required. View course

Algorithms and System Design with GenAI

This course teaches students how to design and build larger software projects in Python, with a focus on solving complex problems through decomposition, testing, and system design. Students will learn to evaluate algorithms and data structures, including trees and graphs, and use Big O notation for efficiency analysis. Throughout the course, students will explore best practices for using generative AI tools to support code generation, debugging, and design reflection. Prior experience with Python and basic CS concepts is required. View course

Introduction to Software Engineering with GenAI

Dive into the future of software development with our project-based course, "Introduction to Software Engineering with GenAI." This course is designed for learners with a basic understanding of Python and computer science who want to build a complete web application from the ground up. Students will learn the entire software development lifecycle—from design and testing to deployment—using the same professional tools and collaborative processes found in the tech industry today. The curriculum places a special emphasis on intelligently integrating Generative AI, teaching not only how to leverage these powerful tools but also how to critically evaluate and troubleshoot their outputs to create robust, high-quality software. View course

Introduction to Product Management with GenAI

This course offers a comprehensive introduction to modern product management, blending essential principles with the power of generative AI. Through hands-on, team-based projects, students will learn to navigate the entire product lifecycle, from initial idea and user research to a successful launch. This curriculum is designed to provide practical experience and prepare students to lead cross-functional teams and drive product success in today's tech landscape. View course