M.S. in Artificial Intelligence
M.S. in Artificial Intelligence
The M.S. program in Artificial Intelligence acclimates students to the ongoing AI revolution that has already produced computer programs with problem-solving and content-generating abilities that complement and enhance human abilities. The program offers theoretical and practical knowledge in various areas of AI, including Natural Language Understanding and Generation, Image Understanding, Reasoning, and Planning. It empowers students to apply AI techniques in a wide range of application domains.
Prerequisites
Applicants should have a bachelor's degree in the general area of Computing, from an accredited University. Applicants with a bachelor's degree in STEM or related professional experience can start with the graduate certificate and then apply to the M.S. program. Further information can be found in the program's webpage.
Degree Requirements
The program requires the completion of 30 credits. These are satisfied by taking 10 courses, as indicated in the following table.
Students in the Master of Science in Artificial Intelligence (MS-AI) program must successfully complete 30 credits based on any of the following options:
- Courses only (30 credits)
- Courses (27 credits) + MS Project (3 credits)
- Courses (24 credits) + MS Thesis (6 credits)
Independent of the chosen option, 4 out of 7 core courses are required (detailed below).
If a student chooses the MS thesis option, the thesis must be related to Artificial Intelligence and requires approval from the Program Director.
Students may choose an elective outside the list after approval of their respective advisor.
| Code | Title | Credits |
|---|---|---|
| Core Courses | ||
| Select at least four of the following: | ||
| Introduction to Big Data | ||
| Reinforcement Learning | ||
| Artificial Intelligence | ||
| Machine Learning | ||
| Deep Learning | ||
| Natural Language Processing | ||
| Trustworthy Artificial Intelligence | ||
| After the 4 core courses are completed, any of the remaining core courses listed can count towards the elective requirements. | ||
| Elective Courses | ||
| Data Mining | ||
| Image Processing and Analysis | ||
| Computer Vision | ||
| Advanced Machine Learning | ||
| High Performance Data Analytics | ||
| Pattern Recognition and Applications | ||
| Python and Mathematics for Machine Learning * | ||
| Selected Topics in Data Science | ||
| Information Theory | ||
| Probability Distributions | ||
| Introduction to Biostatistics | ||
| Statistical Inference | ||
| Statistical Methods in Data Science | ||
| Introduction to Robotics | ||
| Deep Learning in Business | ||
| Project and Thesis Courses | ||
| Master's Project | ||
| Master's Thesis | ||
- *
DS 637 is recommended as an introductory course, offering a review of mathematics for machine learning to students with a limited background in mathematics or programming.
Master's Project and Thesis Policies
The contents of this section apply only to students who elect to do a DS 700B Master's Project or a DS 701B Master's Thesis in topics related to Artificial Intelligence.
Students must first find a research advisor who must be a tenure-track faculty of the DS department, including faculty with a joint appointment. Tenure-track faculty are the department members including those who hold joint appointments with the rank of Assistant Professor, Associate Professor, Professor, and Distinguished Professor.
In order to find a research advisor, students are encouraged to attend special presentations offered by the department or to directly contact professors. Professors may not always have availability for conducting an MS project/thesis. Students are therefore encouraged to start looking for an advisor as early as possible, especially if they are considering pursuing a Master’s Thesis that takes two semesters.
The students must be in close coordination with their research advisor who will determine the topic of the Project/Thesis and guide them to take specific elective courses that will prepare them for the research.
Registration:
- Master’s Project: With permission of their research advisor, students must register in the DS 700B Master's Project course. To register for the Master's Project, students must have completed at least 9 credits and must be in good standing.
- Master’s Thesis: With permission of their research advisor, students must register in the DS 701B Master's Thesis course.
- They must receive a satisfactory (S) grade in DS 700B before DS 701B registration in the immediately following semester, with the same advisor. The MS thesis topic should be continuation of the work done in DS 700B.
Thesis Requirements:
- An MS Thesis Committee must be formed, according to the requirements set forth by the Office of Graduate Studies.
- A written thesis must be submitted. The thesis must adhere to the style requirements set forth by the Office of Graduate Studies.
- An oral defense is required. The defense must take place before the last day of the Examinations.
