Applied Human Centered AI, MS

Contact:

Jeff Saltz
Program Director
(315)-443-2911
igrad@syr.edu

Website

https://ischool.syracuse.edu/academics/applied-human-centered-artificial-intelligence-masters-degree/

Overview:

The 31-credit Applied Human Centered AI Master’s degree prepares students to use advanced machine learning packages and APIs with a human-centered approach across a range of domains (ex. business, government). At the heart of the program is a focus on the intricacies of the human-AI interaction and how to use AI packages (such as OpenAI LLMs), ensuring students are adept at utilizing Generative AI and other deep learning libraries in an ethical and effective manner. With a strong emphasis on hands-on projects, students will conclude the program by creating and reflecting on their application portfolio, showcasing their practical expertise and knowledge. In short, this program is designed to equip students with both the technical AI programming skills and the human-centered perspective needed to build responsible and user-friendly AI applications.

Student Learning Outcomes

After completing the program, students will be able to:

Develop robust AI applications by harnessing deep learning libraries and APIs.
Describe potential ethical considerations that might arise when developing AI applications.
Articulate the complexities of human-AI interaction to improve human-AI collaboration.
Reflect upon and critically assess existing and potential AI applications.

Required Core: 21 Credits

IST 664 - Natural Language Processing 3 credit(s)
IST 675 - Dynamics of Human AI Interaction 3 credit(s)
IST 687 - Introduction to Data Science 3 credit(s)
IST 688 - Building Human-Centered AI Applications 3 credit(s)
IST 691 - Deep Learning in Practice 3 credit(s)
IST 692 - Responsible AI 3 credit(s)
IST 736 - Text Mining 3 credit(s)

Concentrations: 9 Credits

Concentrations allow students to select course work that matches their professional interests and planned career paths.

Students are required to select one concentration below, and complete three classes, or 9 credits, from that concentration.

Data Science

IST 659 - Data Administration Concepts and Database Management 3 credit(s)
IST 686 - Quantitative Reasoning for Data Science 3 credit(s)
IST 707 - Applied Machine Learning 3 credit(s)
IST 718 - Big Data Analytics 3 credit(s)

Cloud Computing

IST 615 - Cloud Management 3 credit(s)
IST 659 - Data Administration Concepts and Database Management 3 credit(s)
IST 714 - Cloud Architecture 3 credit(s)
IST 769 - Advanced Big Data Management 3 credit(s)

Self-Guided

Students can select any three IST graduate-level courses (9 credits) that provide a coherent experience related to Applied HCAI. Students should consult with the program director to ensure the appropriateness of the courses and consider how they will add to their knowledge and skillset. Courses outside of the iSchool must receive permission prior to registration.

Exit Requirement: 1 Credit

Students take IST783 in their last semester of study.

IST 783 - Applied Human Centered AI Portfolio 1 credit(s)