Main Content
Data is changing the way our society makes decisions. AI and Data Science are enabling us to design and develop solutions that help solve complex data-driven problems.
Students in the AI and Data Science Certificate program learn the fundamentals of how to formulate a data-driven AI problem, store, manage, analyze, and model data to turn data into actions.
Who should register
Working professionals with experience in the related field of AI and data analysis as well as young professionals seeking a career in AI and Data Science who have:
- Experience with programming (must) and data analysis (optional)
- College-level basics of statistics, probability theory, linear algebra, calculus (Note: Although we will not thoroughly teach them again, we will review them when they are used)
Learning format
In this program with three modules, one per quarter, we examine concepts, elements, strategies, and skills covering the general discipline of AI and Data Science. The instruction is based on practical examples of AI and Data Science applications in a variety of areas within the industry as well as in academic research.
Building on theoretical foundations from lectures, exercises, discussions and quizzes, students gain hands-on experience through workshops/tutorials with related independent assignments. The series culminates in milestone projects that demonstrate comprehensive AI and Data Science skills.
See Program courses for details.
Technology requirements
Students should have:
- A computer with a recent OS and a current web browser with at least 4GB and preferably 8GB of RAM
- High-speed internet access
- A Google account with Colab access
- Headset and webcam (recommended)
Instructor
Juhua Hu, Ph.D., Associate Professor of Computer Science & Systems
Juhua Hu is also the director of Center for AI and Data Science at the University of Washington Tacoma.
Quick info
Dr. Juhua Hu (juhuah@uw.edu) |
Program Courses
Upcoming session: Winter 2026 cohort
Introduction to AI and Data Science
Wednesdays, January 7 to March 18
Learn how to formulate a data driven problem, conduct data exploration, model the problem with AI, and finally validate for deployment.
No class on February 18
CEUs: 3 (upon successful completion of the course)
Machine Learning
Wednesdays, April 1 to June 10
Learn state-of-the-art machine learning technologies to turn data into actionable insights.
No class on April 15
CEUs: 3 (upon successful completion of the course)
Distributed AI
Wednesdays, June 24 to August 26
Understand distributed data management and computing technologies.
CEUs: 3 (upon successful completion of the course)