Cluster 11
Artificial Intelligence
Instructors:
Yi Zhang, PhD
UCSC Department of Computer Science and Engineering
Xin (Eric) Wang, PhD
UCSC Department of Computer Science and Engineering
Cihang Xie, PhD
UCSC Department of Computer Science and Engineering
Prerequisite: Algebra II or Integrated Math II, Programming
Preferred: Python, Statistics and Probability
This is a FIRST CHOICE cluster option only
Summary: Have you ever used web search engines (e.g., Google, Bing, etc), searched for recommendations for movies, music or production (by Youtube, Amazon, Netflix, Spotify, …), chatted with virtual assistants (e.g., Siri, Alexa, google assistant), or played strategic games (chess, go, etc.)? Would you like to own a self-driving car or household robots in the future? Artificial intelligence (AI), especially machine learning (ML), is the core technology behind these applications.
In this cluster, we will introduce the fundamentals of AI and the applications of ML . You will work on a team project to apply what you learn to an application in social sciences, engineering, business, healthcare, or life sciences. The cluster will start with the basics of Python, the programming language that will be used, and then introduce some common ML packages. Lessons from cluster faculty and guest speakers will help you master the basics of how different ML algorithms work. The course assistants will lead projects where you can gain hands-on experience. This cluster is designed for students with some basic programming experience to further enhance their Python programming skills, as they explore the exciting world of AI.
All students in this cluster will be enrolled in the following courses:
Fundamentals
This will focus on the introduction to AI algorithms and their applications. Topics include supervised learning, unsupervised learning, and online learning. The course will consist of an introduction to standard learning methods, such as logistic regression, neural networks, decision trees, nearest neighbor, K-mean, reinforcement learning, multi task learning techniques. Applications in different domains will be introduced and demonstrated. Lectures will be supplemented with the latest AI research in natural language processing, computer vision and robotics.
Labs and Projects
Students will work in teams to specify, design, develop, evaluate, improve, and document a complete project to apply AI/ML techniques learned in the course to specialized domain applications. Project sessions will be led by course assistants. A formal presentation and demonstration of the projects is required. Projects may be drawn from real world applications, industry, or UCSC campus research.
