George Washington University

How this program compares

At an estimated $84K in total tuition, the Doctor of Engineering in AI and Machine Learning sits about 1% above the $82.9K average for AI doctoral programs in our database — placing it in the 67th percentile on cost among the 42 we track at this level. It is one of the 57% of programs in our database offered fully or partly online.

Admission Snapshot

Typical admitted student: A master's degree in engineering, computer science, or a related field with a minimum GPA of 3.0 is required, along with relevant professional experience in AI or machine learning and strong quantitative background including linear algebra, probability, and programming.

About This Program

This research-based doctoral program provides advanced expertise in AI and machine learning, focusing on applying cutting-edge techniques to solve real-world engineering challenges. Coursework concentrates on Generative AI and LLMs and Natural Language Processing (NLP). Most students complete it in about 2 years.

Estimated total tuition is $84K, above the $82.9K average for AI doctoral programs in our database and in the 67th percentile on cost at this level. Applicants should weigh that premium against the program's outcomes and brand.

Pursue advanced AI Research Scientist in Engineering AI through generative ai and llms Graduates frequently move into roles such as AI Research Scientist, with reported salaries around $180,000.

Career Outcomes

Pursue advanced AI Research Scientist in Engineering AI through generative ai and llms

• 1. AI Systems Architect
• 2. Machine Learning Director
• 3. Principal AI Engineer
• 4. Research Engineer in AI

What You'll Learn

• Design and deploy scalable AI systems for engineering applications.
• Develop advanced machine learning models for real-world data challenges.
• Apply deep learning techniques to computer vision and natural language processing.
• Engineer ethical and robust AI solutions integrating engineering principles.

Curriculum Highlights

The 48-credit program consists of 24 credits of required coursework in subjects like reinforcement learning and analytical methods, followed by 24 credits of praxis research.

Top Employers

Top employers include tech leaders like Google, Amazon, Microsoft, and engineering firms such as Lockheed Martin and Boeing.

Admissions

A master's degree in engineering, computer science, or a related field with a minimum GPA of 3.0 is required, along with relevant professional experience in AI or machine learning and strong quantitative background including linear algebra, probability, and programming.

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 3
• Resume: Required
• Transcripts: Official transcripts required

Academic Requirements

• Degree Required: Master's degree
• GRE/GMAT: Optional
• TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)