Applied Human-Centered Artificial Intelligence
Master’s Degree

ON CAMPUS PROGRAM

Earn your master’s degree in AI.

With a master’s degree in Artificial Intelligence, you’ll learn to apply advanced machine learning models ethically and with a human-centered approach. Our applied program means you’ll get hands-on experience with LLMs, develop robust applications, and graduate with a portfolio demonstrating your expertise.

  • Use deep learning models to develop robust applications.
  • Use Python to integrate and leverage public generative AI APIs.
  • Explore ethical implications and improve human-AI collaboration.
  • Pursue a career in one of today’s fastest-growing, most in-demand fields.
  • Complete your master’s degree in artificial intelligence in as little as one year.
Quick Info

Next term starts Spring 2025, on campus.

11 Courses / 31 Total Credit Hours

What can I do with a master’s in artificial intelligence?

A master’s degree in AI opens doors to careers across industries. Analyze consumer behavior as a marketing analyst. Improve outcomes in the healthcare industry. Develop new applications at a tech startup. With this leading-edge degree you’ll have in-demand skills and knowledge, and great earning potential.

SAMPLE JOB TITLES
  • Machine learning engineer
  • Data scientist
  • Software engineer
  • Business intelligence developer
  • Research scientist
  • Big data architect
  • AI engineer
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FASTEST-GROWING
FIELD IN THE USA
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Average Salary for AI experts
Glassdoor.com
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Job growth in AI
positions in 2024
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Courses & Curriculum

The master’s degree in artificial intelligence is 31 credits and can be completed in as little as one year. The curriculum combines a primary core, the choice of three tracks for your secondary core, and electives to give you a strong data science foundation with a focus of your choosing.

Primary Core – 21 Credits

IST 664 | 3 CREDITS
Crosslisted with CIS 668
Linguistic and computational aspect of natural language processing technologies. Lectures, readings, and projects in the computational techniques required to perform all levels of linguistic processing of text. Additional work required of graduate students.

IST 675 | 3 CREDITS
This class focuses on understanding, analyzing, and critiquing scientific and practical perspectives on what counts as “interactivity” and what counts as “intelligence” when AI-driven actors interact with humans.

IST 687 | 3 CREDITS
Introduces information professionals to fundamentals about data and the standards, technologies, and methods for organizing, managing, curating, preserving, and using data. Discusses broader issues relating to data management, quality control and publication of data.

IST 688 | 3 CREDITS
Learn to build Generative AI applications leveraging large language models. Through hands-on projects, students will use libraries and APIs to create conversational agents, Q&A bots, and goal-oriented assistants.
PREREQ IST 687 or knowledge of Python Programming

IST 691 | 3 CREDITS
Introduction to Deep Learning concepts and techniques required to develop Deep Learning based applications. Hands-on experience applying models using open-source frameworks and packages.
PREREQ IST 687 OR IST 387 (B grade or higher)

IST 692 | 3 CREDITS
This course will provide students the critical skills necessary to discuss and evaluate more just and equitable AI models, as well as leverage Python or R packages to build such models.
PREREQ IST687 OR IST387 (B grade or higher)

IST 736 | 3 CREDITS
Introduces concepts and methods for knowledge discovery from large amount of text data, and the application of text mining techniques for business intelligence, digital humanities, and social behavior analysis

Secondary Core – 9 Credits

Students select 3 courses (9 credits) from one of the tracks below.

Data Science

IST 659 | 3 CREDITS
Definition, development, and management of databases for information systems. Data analysis techniques, data modeling, and schema design. Query languages and search specifications. Overview of file organization for databases. Data administration concepts and skills.

IST 659 | 3 CREDITS
Definition, development, and management of databases for information systems. Data analysis techniques, data modeling, and schema design. Query languages and search specifications. Overview of file organization for databases. Data administration concepts and skills.

IST 659 | 3 CREDITS
Definition, development, and management of databases for information systems. Data analysis techniques, data modeling, and schema design. Query languages and search specifications. Overview of file organization for databases. Data administration concepts and skills.

IST 659 | 3 CREDITS
Definition, development, and management of databases for information systems. Data analysis techniques, data modeling, and schema design. Query languages and search specifications. Overview of file organization for databases. Data administration concepts and skills.

Cloud Computing

IST 616 | 3 CREDITS
Cloud services creation and management. Practical experience in using, creating and managing digital services across data centers and hybrid clouds. Strategic choices for cloud digital service solutions across open data centers and software defined networks.

IST 659 | 3 CREDITS
Definition, development, and management of databases for information systems. Data analysis techniques, data modeling, and schema design. Query languages and search specifications. Overview of file organization for databases. Data administration concepts and skills.

IST 714 | 3 CREDITS
Advanced, lab-based exploration of enterprise cloud migration/adoption costs, planning and economics; cloud application/service design, network and data center resource orchestration. Topics also include cloud elastic sizing, risk management, governance, compliance and monitoring.

IST 769 | 3 CREDITS
Analyze relational and non-relational databases and corresponding database management system architectures. Learn to build complex database objects to support a variety of needs from big data and traditional perspectives. Data systems performance, scalability, security. Additional work required for graduate students.

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 the electives will add to their knowledge and skillset.  Courses outside of the iSchool must receive permission prior to registration to be used as secondary core credit.

Exit requirement

IST 783 | 1 CREDIT

Project based activity for which students choose assignments and projects worked on in courses during their studies, and then reflect on their abilities specified in the program learning outcomes. .

Gain Experience.

Complement your master’s degree in AI with real-world experience. From student-led consulting projects to research endeavors, internships, networking events and more, we connect you with the experts and the expertise to take the next step in your career.

Grow Your Potential.

In addition to getting practical, on-the-job experience, you’ll have opportunities to join a research lab or collaborate with faculty on their academic work. Your focus on AI will mean your skills will be in-demand on almost any iSchool research team.

Expand Your Career.

Our dedicated Career Services team is available throughout your program and after. From resume and cover letter prep to interview training, career advising, and alumni and employer connections, you’ll have the support you need to land your dream job.

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