DePaul's 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.

Degree Requirements

 

Careers

• 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).

92%of reporting School of Computing master’s graduates were employed, continuing education, or not seeking employment within six months of graduation

$75,000median salary reported by School of Computing master’s graduates six months after degree completion

Curriculum Requirements

Introductory Courses

No Introductory Course may be substituted for any other course at any level.

Introductory courses may be waived for any of the following conditions based on faculty review:

• The student has the appropriate course work to satisfy an Introductory Course based on an official transcript review by faculty and successful grades, typically B or better.
• The student has appropriate and verified professional experience to satisfy an Introductory Course which is demonstrated through successful completion of a GAE exam.
• If a Graduate Assessment Examination (GAE) is available for the Introductory Courses, upon successfully completion of a GAE, a waiver will be issued.

•  CSC 412 Tools and Techniques for Computational Analysis
•  IT 403 Statistics and Data Analysis
•  CSC 400 Discrete Structures for Computer Science
•  CSC 401 Introduction to Programming
•  CSC 402 Data Structures I
•  CSC 403 Data Structures II

Required Courses

•  CSC 480 Artificial Intelligence I
•  CSC 580 Artificial Intelligence II
•  CSC 421 Applied Algorithms and Structures
•  CSC 481 Introduction to Image Processing
•  DSC 540 Advanced Machine Learning
•  CSC 583 Natural Language Processing
•  CSC 484 Ethics in Artificial Intelligence
•  CSC 587 Cognitive Science
•  CSC 578 Neural Networks and Deep Learning

Capstone Requirement

Choose one courses from the following list:

•  CSC 675 Capstone in Artificial Intelligence
•  CSC 695 Master's Research

A student who is working on a research project and has made an original contribution to their area of study may choose to complete a Master's Thesis. Additional information and requirements for School of Computing students pursuing the thesis option can be found on the SoC Master's Thesis Guideline page.

Major Electives

Choose two courses from the following list:

•  DSC 450 Database Processing for Large-Scale Analytics
•  CSC 555 Mining Big Data
•  CSC 482 Applied Image Analysis
•  CSC 528 Computer Vision
•  CSEC 440 Information Security Management (Formerly CNS 440)
•  DSC 480 Social Network Analysis
•  DSC 478 Programming Machine Learning Applications
•  CSC 575 Intelligent Information Retrieval
•  CSC 577 Recommender Systems
•  CMNS 549 Special Topics in Organizational Communication *
•  CSC 475 Introduction to Robotics
•  CSC 594 Topics in Artificial Intelligence
•  CSC 458 Symbolic Programming

*For CMNS 549, only accepdiv topic is Core Business Communication Functions and Skills

Open Electives

Student must complete 1 advisor-approved graduate course from the School of Computing in the range of 421-699.

 

Degree Requirements

Students in this degree program must meet the following requirements

• Complete a minimum of 52 graduate credit hours in addition to any required introductory courses of the designated degree program.
• Complete all graduate courses and requirements listed in the designated degree program.
• Earn a grade of C- or better in all courses of the designated degree program.
• Maintain a cumulative GPA of 2.5 or higher.
• Students pursuing a second (or more) graduate degree may not double count or retake any course that applied toward the completion of a prior graduate degree. If a required course in the second degree was already completed and applied toward a previous degree, the student must meet with a faculty advisor to discuss a new course to be completed and substituted in the new degree. This rule also applies to cross-listed courses, which are considered to be the same course but offered under different subjects.
• Students pursuing a second master's degree must complete a minimum of 52 graduate credit hours beyond their first designated degree program in addition to any required introductory courses in their second designated degree program.

Students with a GPA of 3.9 or higher will graduate with distinction.

For DePaul's policy on repeat graduate courses and a complete list of academic policies see the DePaul Graduate Handbook in the Course Catalog.