CS106EA will provide students with an overview of Artificial Intelligence and understanding of key AI concepts. We will examine a typical Machine Learning pipeline. We'll study different problems that ML is used to solve and common issues that arise (such as overfitting, drift, and bias). Students will learn how neural networks work and then examine specialized versions of neural networks for processing images, sequence data, and text. We'll explore generative AI systems for text and images. We'll also study societal issues related to Artificial Intelligence including ethical considerations and the implications of automation. This course will focus on providing a conceptual understanding of AI. While students will get some hands-on time working with and modifying actual artificial intelligence systems, it is not a programming class. However, students should have CS 106A or comparable experience as we'll be assuming some basic understanding of programming.
3 units · Letter or Credit/No Credit
CS106EA will provide students with an overview of Artificial Intelligence and understanding of key AI concepts. We will examine a typical Machine Learning pipeline. We'll study different problems that ML is used to solve and common issues that arise (such as overfitting, drift, and bias). Students will learn how neural networks work and then examine specialized versions of neural networks for processing images, sequence data, and text. We'll explore generative AI systems for text and images. We'll also study societal issues related to Artificial Intelligence including ethical considerations and the implications of automation. This course will focus on providing a conceptual understanding of AI. While students will get some hands-on time working with and modifying actual artificial intelligence systems, it is not a programming class. However, students should have CS106A or comparable experience as we'll be assuming some basic understanding of programming.
Offered in Autumn 2026, Winter 2027 at Stanford University.