Online Doctor of Engineering in Artificial Intelligence & Machine Learning

Applications for the January 2026 cohort are now open. The deadline to submit an application including official transcripts is November 30, 2025.

Program Description

The online Doctor of Engineering in Artificial Intelligence & Machine Learning is a research-based doctoral program. The program is designed to provide graduates with a solid understanding of the latest AI&ML techniques, as well as hands-on experience in applying these techniques to real-world problems. Graduates of this program are equipped to lead AI&ML projects and teams in a wide range of industries, including healthcare, finance, and manufacturing. Having developed advanced research skills, graduates are also well-prepared for academic research and teaching roles.

Curriculum

The degree requires completion of six graduate-level courses (listed below) and a minimum of 24 credit hours of Praxis Research (SEAS 8588). During the research phase, the student writes and defends a research praxis on a topic related to AI&ML. The topic is selected by the student and approved by the research advising committee.

Learn More About the Courses

SEAS 8505 Applied Machine Intelligence and Reinforcement Learning: Theory and practice of machine learning leveraging open-source tools, algorithms and techniques. Topics include intelligent model training, support vector machines, deep learning, transformer methods, GANs, and reinforcement learning. (4 credit hours)

SEAS 8510 Analytical Methods for Machine Learning: Mathematical tools for building machine learning algorithms: linear algebra, analytical geometry, matrix decompositions, optimization, probability and statistics (4 credit hours)

SEAS 8515 Data Engineering for AI: Developing Python scripts to automate data pipelines, data ingestion, data processing, and data warehousing. Machine learning applications with Python including text mining and time series analysis. (4 credit hours)

SEAS 8520 Deep Learning and Natural Language Processing: Fundamentals of deep learning and Natural Language Processing (NLP). Techniques for designing modern deep learning networks using Keras and TensorFlow. NLP topics include sentiment analysis, bag of words, TFIDF, and Large Language Models. (4 credit hours)

SEAS 8525 Computer Vision and Generative AI: Explore AI's visual realm. Learn image processing object detection, and models in generative adversarial networks and neural networks. Master tools for creating AI applications in art, design, ethical considerations, and societal impacts of generative AI technology. (4 credit hours)

SEAS 8599 Praxis Development for AI & Machine Learning: Overview of research methods. Aims and purpose of the praxis. Development of praxis research strategies, formulation, and defense of a praxis proposal. (4 credit hours)

SEAS 8588 Praxis Research for D.Eng. in AI & Machine Learning: Research leading to the degree of Doctor of Engineering in AI and Machine Learning. (24 Credit Hours)  

Admissions Process

Review the Admissions Requirements

• Bachelor’s and master’s degrees in engineering, applied science, business, computer science, or a related field from accredited institutions.
• A minimum graduate-level GPA of 3.2
• Capacity for original scholarship.
• TOEFL, IELTS, Duolingo, or PTE scores are required of all applicants who are not citizens of countries where English is the official language.  Check our International Students Page to learn about the SEAS English language requirements and exemption policy. Test scores may not be more than two years old.

Note: GRE and GMAT scores are not required

Please note that our doctoral programs are highly selective; meeting minimum admissions requirements does not guarantee admission.  

Apply for Admission and Submit Supporting Documents

Apply for Admission

• Attach up-to-date Resume 
• Attach Statement of Purpose – In an essay of 250 words or less, state your purpose in undertaking graduate study at The George Washington University. Describe your academic objectives, research interests, and career plans. Discuss your qualifications including collegiate, professional, and community activities, and any other substantial accomplishments not mentioned.
• Send Official Transcripts – Official transcripts are required from all institutions where a degree was earned. Transcripts should be sent electronically to %20aidoctorategwu [dot] edu (aidoctorate[at]gwu[dot]edu) or via mail to:

Online Engineering Programs
The George Washington University
PO Box 2717
Laguna Hills, CA 92654

Normally, all transcripts must be received before an admission decision is rendered for the Doctor of Engineering program. 

Remain Engaged in the Admissions Process

You will receive emails from us updating you as your application goes through the admissions process.