30 credit hours
Artificial intelligence is one of the top growth areas in research and tech industry and is projected to continue growing in size and importance for the foreseeable future. The MAS-AI program is designed to meet local, national, and global needs for artificial intelligence professionals. The course of study teaches the foundational concepts, methods, and skills of artificial intelligence, machine learning, and big data analytics, as well as the mathematical foundations, ethics, and AI application areas needed for professional success in the area. The program was designed by a committee of AI experts in the CS department, with reference to the current and projected job market in AI, comparison with other similar programs, and consultation with industry representatives.
The Master of Artificial Intelligence (MAS-AI) is a Professional Master's degree program designed for:
- Computer science professionals currently working in business, government, or industry who want to advance their careers.
- Recent computer science graduates who want to extend and deepen their knowledge of artificial intelligence in order to gain a competitive edge in the job market.
- People without a previous degree in computer science who want to prepare for a career as a working artificial intelligence professional.
The MAS-AI program provides a conceptual and practical education in Artificial Intelligence and its subfields of Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Probabilistic Reasoning, Data Analytics, and Data Mining. The program has a rigorous core curriculum and allows in addition students to select courses based on interest. Students in the MAS-AI program can choose to do a Master's Project (but not a Master's Thesis) or coursework-only. There is no master's comprehensive exam.
A full-time student whose bachelor degree was in computer science can complete the MAS-AI program in three semesters plus a summer course. A student without a bachelor's degree in computer science may require extra time to make up deficiencies in prerequisite undergraduate coursework.
Graduate CS classes in this program are offered during the day and evening, and both day-only and evening-only student schedules can be accommodated. Students can complete the MAS-AI program as online distance students; classes can be taken entirely through on-demand Internet, without ever visiting the IIT campus.
In general, for admission into the MAS-AI program, prospective students need a bachelor's degree (not necessarily in computer science) and are required to submit a transcript and possibly GRE and TOEFL scores. For more information about this program, contact Dr. Mustafa Bilgic. Admission requirements are listed below.
- GPA 3.0
- GRE 304
- TOEFL – the university standards and requirements
- Grades of "B" or better in the Prerequisite Coursework Requirements below, for applicants whose bachelor degrees are not in Computer Science.
Completing the MAS-AI degree program requires:
- A minimum total of 30 credit hours of coursework approved by an adviser.
- A GPA of at least 3.0/4.0 in the plan of study.
Coursework used to meet degree program requirements must meet the following restrictions:
- It must include at least two courses in each of two core areas of AI Foundations and AI Applications, as well as one course in each of two core areas of Data Analytics and Data Processing. It must also include at least one Interdisciplinary Elective.
- There are in addition three free electives that may come from any of the core groups or any other 400-500 level CS or CSP course.
- At least 18 of the total credit hours must be in CS or CS Professional (CSP) courses, from the IIT CS department (no transfer courses).
- At least 20 of the total credit hours must be at the 500-level.
- The remaining 10 credit hours may include CS or CSP courses (at the 400-level or above) and transfer credit for coursework from other IIT departments or for CS courses from other universities.
- At most 6 of the total credit hours can come from "short", accelerated courses.
- Co-terminal students can share 9 credits of coursework with their bachelor's studies. (See details.)
- At most 3 of the total credit hours can come from the optional master's project (CS 597). Credit hours from a master's thesis (CS 591) cannot be used.
- Interprofessional Projects (IPROs) and deficiency courses (CS 201, 401, 402, and 403) cannot be applied toward the credit hour requirement.
- All other relevant university and college requirements (such as time limits to graduate) must be met.
A student whose cumulative GPA falls below 3.0/4.0 falls out of good standing and is placed on academic probation. The CS department will not approve applications for graduate internships, CPTs, and OPTs for students on academic probation. In addition, students may not take more than 9 credit hours per semester while on academic probation. The Graduate College requires students on academic probation to file an Academic Probation Contract (Form 702) before being allowed to register for more classes. For more Graduate College policies on academic probation, see the Graduate Bulletin > Academic Policies.
- International master's students (students on F-1 visas) may be eligible for Curricular Practical Training (CPT) while studying for a degree and Optional Practical Training (OPT) after completion of a degree. Information and forms are available from the Career Management Center (CMC) and the International Center.
- The CS department is firm on the requirements of a grade point average (GPA) of at least 3.0 to be eligible for a CPT or OPT. Students who do not meet this criterion should consult with the International Center to discuss their options. Note that a GPA falling below 3.0 will cause eligibility for a CPT to be revoked, even if permission forms have already been signed.
- A student must complete 18 credit hours of coursework to be eligible for a CPT. In addition, the CS department requires second degree and transfer students to complete at least 9 credits of IIT CS coursework before they can be eligible for a CPT.
Course of Study
Required Core Courses for MAS-AI
There are four categories of core courses: AI Foundations, AI Applications, Data Analytics, Data Processing, and one category of Interdisciplinary Electives. The core areas of AI Foundations and AI Applications require students to take at least two courses in each category whereas the core areas of Data Analytics, Data Processing require students to take at least one course in each category. The category of Interdisciplinary Electives requires students to take at least one course in it.
Note: Only courses taken at IIT can be used as core courses; courses transferred from other universities can be used only as electives.
Core course groups
AI Core (6 credits)
- CS 480 Introduction to Artificial Intelligence or CS581 Advanced Artificial Intelligence
- CS 584 Machine Learning or MATH 569 Statistical Learning
AI Applications (6 credits)
Data Analytics (3 credits)
- CS 522 Advanced Data Mining
- CS 578 Interactive and Transparent Machine Learning
- CS 583 Probabilistic Graphical Models
- CS 595 Deep Learning
- CSP 554 Big Data Technologies
- CSP/MATH 571 Data Preparation and Analysis
- MATH 564 Applied Statistics
- MATH 574 Bayesian Computational Statistics
Data Processing (3 credits)
- CS 520 Data Integration, Warehousing, Provenance
- CS 525 Advanced Database Organization
- CS 546 Parallel and Distributed Processing
- CS 554 Data-Intensive Computing
Interdisciplinary Electives (3 credits)
- BIOL 440 Neurobiology
- BIOL 550 Bioinformatics
- BME 433 Biomedical Engineering Applications of Statistics
- BME 504 Neurobiology
- COM 501 Introduction to Linguistics
- COM 584 Humanizing Technology
- ECE 563 Computational Intelligence in Engineering
- MMAE 440 Introduction to Robotics
- MMAE 540 Robotics
- MSF 526 Computational Finance
- PHIL 574 Ethics in Computer Science
- PSYC 423 Learning Theory
- PSYC 426 Cognitive Science
- PSYC 503 Learning and Cognition
Additional electives from other departments will be evaluated as relevant graduate level courses become available.