CS232: Artificial Intelligence
Artifical Intelligence is the study of how to build computer programs that can perform tasks like humans. This course traces the development of the field from the symbolic, knowledge-rich approaches of 20th century AI (e.g., rule-based systems), to statistical approaches that rely on increasingly large amounts of data, including an overview of contemporary deep learning techniques.
We will explore how to apply these techniques in several AI application areas, including robotics, computer vision, and natural language processing, and consider ethical issues related to AI's impact on society.
Learning Goals
+ Learn about a range of AI approaches, including rule-based/symbolic systems, statistical approaches, machine learning, and deep learning.
+ Learn to recognize and choose appropriate techniques for a range of problems, including search, classification, and generation.
+ Implement AI techniques in a variety of domains, including game-playing, robotics, computer vision, and natural language processing.
+ Evaluate AI models with respect to both scientific validity and societal impact.
+ Critically consider the ethical consequences of current and future AI technology.
Q&A
You can submit anonymous questions here: Question Form
You read the CS 232 Q&A here: Q&A
Instructor: Carolyn Anderson
Tutors:
Aeka Tomita, Amber Wu, and Coco Zhang