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 the performance of 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: Lepei Zhao & Lyra Kalajian

Grader: Jess Yao

Lecture

Time: T F 8:30-9:45am

Location: SCI L043

Help hours:

Time: M Th 4-5:30pm

Location: SCI W422

Lyra's hours:

TBA

Lepei's hours:

TBA