Online Doctor of Engineering in Artificial Intelligence & Machine Learning
We are now accepting applications for the cohort beginning in January 2024.
The application deadline is November 15, 2023.
Visit the Application Page to apply
Introduction
The D.Eng. in Artificial Intelligence and Machine Learning program addresses the widespread and growing need for practitioners who can learn advanced artificial intelligence concepts and tools and apply that knowledge in real-world systems and applications. We became aware of this need in part based on the offering of our master’s and doctoral degrees in cybersecurity, cloud computing management, and engineering management and systems engineering. Alumni from these programs and other leaders in industry and government have expressed the need for a doctoral program that provides working professionals additional technical depth and a terminal degree that recognizes their expertise and standing in their field.
A Doctor of Engineering (D.Eng.) in Artificial Intelligence and Machine Learning (AI & ML) is a research-focused doctoral degree program that aims to prepare graduates for leadership roles in industry and academia. This program is designed to provide students with a deep understanding of the latest AI and machine learning techniques, as well as hands-on experience in applying these techniques to real-world problems.
Graduates of this program are equipped to lead AI and machine learning projects and teams in a wide range of industries, including healthcare, finance, manufacturing, and more. They are also well-prepared for academic research and teaching roles, as they will have developed advanced research skills and the ability to communicate complex ideas to a variety of audiences.
Program Objectives
The objectives of the Doctor of Engineering in Artificial Intelligence and Machine Learning are to ensure that graduates:
- Master advanced theory and practice for building state-of-the-art AI and machine-learning models.
- Understand the societal and ethical impacts of AI.
- Lead their organization in building and scaling AI for maximum business impact.
Program Format
The degree requires 24 credit hours of graduate level courses and a minimum of 24 credit hours of research during which the student writes and defends a praxis paper on a topic related to Artificial Intelligence and Machine Learning, chosen by the student and approved by the advising committee.
Classroom Phase
Course sessions last 10 weeks. Classes meet Saturday mornings from 9:00 am-12:00 pm and afternoons from 1:00-4:00 pm (all times Eastern). This program is taught in an accelerated, cohort format in which students take all courses in lock step. Attendance at all class meetings is expected, and students must remain continuously enrolled; i.e., leaves of absence are permitted only in medical or family emergency, or in case of deployment to active military duty.
| Session | #Course | #Credit Hours | Tentative Dates |
| Fall-1 2023 | 2 | 6 | August 12 – October 14, 2023 |
| Fall-2 2023 | 2 | 6 | October 28, 2023 – January 20, 2024 |
| Spring-1 2024 | 2 | 6 | February 3 – April 6, 2024 |
| Spring-2 2024 | 2 | 6 | April 20 – June 22, 2024 |
* No classes on Memorial Day, Thanksgiving, Christmas, and New Year Weekends
Research Phase
Upon successful completion of the classroom phase, students are registered for a minimum of 24 credit hours (ch) of SEAS 8588 Praxis Research: 3 ch in Summer 2024, 9 ch in Fall 2024, 9 ch in Spring 2025 and 3 ch in Summer 2025. Throughout the research phase, the student develops the praxis on an advisor-approved topic related to Artificial Intelligence and Machine Learning. Faculty research directors meet with students at least once per month.
Research Areas for Praxis
The following are examples of the research areas that our current students are pursuing:
- Developing algorithms and methods that can explain how AI systems reach their decisions or predictions, making them more transparent and trustworthy
- Investigating how reinforcement learning can improve robotic performance and control, particularly in complex environments
- Examining how to ensure that AI systems are fair and unbiased in their decision-making, particularly in areas such as hiring, lending, and criminal justice
- Developing more advanced natural language processing models and algorithms that can understand and interpret human language more accurately and effectively/li>
- Investigating how to apply transfer learning techniques to improve the performance of AI systems in new and different domains, with less data and less training time
Graduation and Scholarship Requirements
To meet graduation requirements, D.Eng. students can have no grades below B-, and must complete the classroom phase of the program with a GPA of 3.2 or higher. If a doctoral student receives any grade below B-, graduate study is terminated and further enrollment is prohibited.
Tuition
All classes meet live online through synchronous distance learning technologies. Classes are recorded for future viewing. Tuition is $1750 per credit hour for the 2023-2024 year. A non-refundable tuition deposit of $995, which is applied to tuition in the first semester, is required when the student accepts admission.
Visit the Application Page to apply
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