Computer Science

How RNNs (Recurrent Neural Networks) + Transformers Work

This assignment, by AI4ALL, is from the RNNs & Transformers Google Drive, which also includes all the related materials for the activity. The assignment includes standards for K12 students, but it can easily be used in the college classroom as well. The Summary from the site explains: This curriculum is meant to be an introductory hands-on deep …

How GANs (Generative Adversarial Networks) Work

This assignment, by AI4ALL, is from the GANs Google Drive, which also includes all the related materials for the activity. The assignment includes standards for K12 students, but it can easily be used in the college classroom as well. The Summary from the site explains: This is a technical curriculum about how some AI systems that generate …

Generate: Software Coding

This assignment, by Kevin Yee, Kirby Whittington, Erin Doggette, and Laurie Uttich, is from the book ChatGPT Assignments to Use in Your Classroom Today. The Summary from the site explains: Provide students with the opportunity to transform concepts and ideas into products and solutions by using AI tools to generate software codes. Key Features of This Assignment …

Build a Brain: Coin Snap

This assignment, by Peter McOwan and Paul Curzon, is from the Computer science activities with a sense of fun from Queen Mary University of London. The Summary from the site explains: Each neuron [in the human brain] follows simple rules, a simple algorithm, that tell it when to fire. [In this activity, students] can make [their] own …

The Intelligent Piece of Paper

This assignment, by Peter McOwan and Paul Curzon, is from the Computer science activities with a sense of fun from Queen Mary University of London. The Summary from the site explains: Hold a competition between a human and an artificial intelligence: a “highly intelligent piece of paper.” In this ongoing challenge between the best of humanity and …

cmpttnl cnstrnt: An Exercise in Constraint and Prompt Engineering

This assignment, by Douglas Luman, is from the TextGenEd collection in the WAC Clearinghouse Repository. The Abstract from the site explains: As new context-aware generative models challenge the human relationship to language, students benefit from first-hand observation of these models’ successes and limitations. Using these models often requires using “prompts” (natural language-based directions) to guide their output. …