MS in artificial intelligence (AI) will prepare you for a successful career in this fast-growing field. You will gain advanced technical skills and a deep understanding of concepts and techniques in artificial intelligence and machine learning to build and support AI empowered systems.
DePaul is a perfect place to earn your master’s degree in artificial intelligence:
A degree focused on a high-growth field. The AI field is growing in leaps and bounds. With an MS in artificial intelligence from DePaul, you can grow with it. Learn how to create complex intelligent systems and integrate AI techniques into existing applications and processes. Explore a wide range of relevant technical areas, including natural language processing, big data systems, computer vision, image processing, robotics and cybersecurity.
DePaul’s leadership, your advantage. DePaul is among the first and few to offer an MS in artificial intelligence. Our leadership in the field is not new—we have had active programs in AI-related areas for more than 20 years. Here, you’ll gain the technical knowledge and skills that AI-focused employers are looking for.
The DePaul difference. This is a professional master’s degree, reflecting DePaul’s focus on practical, real-world learning. Small cohorts mean you’ll get personal attention from faculty, many of whom are renowned for their research in the AI and computer science fields. And with courses offered both on campus and online, you can choose the format that best fits your schedule and learning style. This is the DePaul difference, here to provide your path to success in AI.
- AI and Machine Learning Specialists are the
#1 emerging, high-demand jobs in the US (2020 World Economic Forum).
- AI Engineering is a
top strategic technology trend for 2021 and beyond (Gartner, 2020).
- AI technologies are projected to
boost corporate profitability in 16 industries across 12 economies by an average of 38% by 2035 (Accenture Research, 2017).
93% of reporting School of Computing master’s graduates were employed, continuing education, or not seeking employment within six months of graduation
Professor Bamshad Mobasher is the director of the Center for Web Intelligence and the co-founder of the Center for Data Science at DePaul. His general research areas include artificial intelligence and machine learning. Dr. Mobasher is considered one of the leading authorities in Web mining, Web personalization, and recommender systems.
Associate Professor Clark Elliott is one of the founding contributing members of DePaul's neuroscience program and a founding faculty member of the Artificial Intelligence program. Over the course of thirty years at DePaul, Dr. Elliott has developed and taught dozens of distinct courses in computer science, cognitive science and ethics with an emphasis on symbolic artificial intelligence and cognitive modeling.
Associate Professor Noriko Tomuro has been teaching at DePaul for more than twenty years. Her research interests are in artificial intelligence; in particular, natural language processing, information retrieval, and machine learning.
In addition to the many teaching and general purpose labs, CDM houses several labs designated to specific research areas that are equipped with advanced technology, software and experimental tools to support faculty and students in their research endeavors.
AI & Personalized Recommender Systems
Professor Mobasher and his team are engaged in cutting edge research in personalized recommender systems. Recommender systems use machine learning and AI to model user preferences and provide personalized information access, supporting e-commerce, social media, news, music and video streaming and other applications where the volume of content would otherwise be overwhelming. It should not be surprising that some of the most effective providers of on-line information and services including Amazon, LinkedIn, Netflix, Facebook, Spotify, Google, and Apple rely on recommender systems technologies as a core part of their underlying systems.
Faculty and students of the Medical Informatics (MedIX) research lab have developed AI novel solutions to challenging data problems in the medical field.
Dr. Peter Hastings and a group of students are developing methods for automatically identifying the causal structure of students’ explanatory scientific essays.
This degree can be completed entirely online. One hundred percent of the program’s lectures—from audio and video to whiteboard writing and supplemental materials—are captured and available online.
How can AI scientists harness the fabulous benefits of AI without wreaking chaos on our world? Discover how to build ethical and trustworthy AI systems in the new Ethics in AI course developed by
Prof. Clark Elliott.
Great for Career Changers
We value students from a wide variety of academic backgrounds so we don’t require a bachelor’s degree in computer science or a related field. We offer introductory courses specifically designed to provide all the preparation you need to be successful in the degree and in your career.
|Enrollment Quarter||Domestic Student Deadline||International Student Deadline|
|Fall||August 1||June 15|
|Winter||December 1||October 15|
|Spring||March 1||January 15|
|Summer||May 1||April 15|
The graduate application process involves completing an online application, sending in your transcripts and submitting any supplemental material (e.g., letters of recommendation, certifications, etc.). To learn more about your program specific requirements, visit our
Graduate Admission page.
Contact Graduate Admission