Online Master of Engineering in Artificial Intelligence and Machine Learning

Master’s Degree in Artificial Intelligence

The Master’s Degree in Artificial Intelligence is designed for professionals seeking to advance their expertise in the data science, algorithms, and computational methods that underpin artificial intelligence and machine learning systems while continuing their careers. Offered in a flexible online format, the program delivers rigorous, graduate-level instruction in core AI and machine learning concepts, with an emphasis on intelligent systems, advanced algorithms, and real-world engineering applications. Guided by expert faculty, graduates are prepared to develop, analyze, and deploy AI-driven technologies and pursue advanced roles across technology, finance, healthcare, transportation, or further academic study.

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Program Overview

Through graduate-level coursework, students engage in an in-depth artificial intelligence and machine learning curriculum that emphasizes mathematical foundations, advanced algorithms, and applied problem-solving from an engineering perspective. The program integrates theoretical principles with practical application, enabling students to design intelligent systems, engineer and deploy machine-learning–driven solutions, and apply neural networks and other AI techniques across diverse domains.

Taught by expert faculty, the program prepares graduates to advance into specialized professional roles and contribute to the engineering and development of AI-driven technologies while considering ethical implications and societal impact. The degree also provides a strong academic foundation for students interested in doctoral study or advanced research in artificial intelligence, machine learning, or related fields.

How Much Does This Degree Cost?

Tuition for the online Master’s Degree in Artificial Intelligence is $1,200 per credit hour for the 2025-2026 academic year. With 30 total credit hours, the estimated total tuition cost is $36,000, billed per semester based on enrolled courses.

A $495 non-refundable tuition deposit is required upon admission and is applied toward first-semester tuition. The program includes no additional fees, and required eBooks and software are provided at no extra cost. Student veterans, military personnel, and eligible dependents are encouraged to inquire about available military education benefits.

How Long Does the Program Take, and How Is It Delivered?

The online Master’s in Artificial Intelligence can be completed in as little as one year for full-time students, with part-time options available. Courses are delivered fully remote and combine live, scheduled instruction with asynchronous coursework.

Quick facts (bulleted list):

• Format: 100% online
• Class schedule: One evening per week (Monday-Thursday), 6:30-9:50 p.m. ET
• Session length: Nine-week sessions
• Enrollment structure: Students enroll in four nine-week sessions, with an optional fifth summer session
• Start options: Up to five start terms per year

Curriculum Highlights

The curriculum consists of 10 courses (30 total credit hours) designed to build advanced expertise in artificial intelligence and machine learning across core areas of the field. Courses combine synchronous and asynchronous learning, providing live instruction alongside flexible coursework.

Learn more about the courses 

ECE 6210 Machine Intelligence: Machine learning theory; classification and linear models; perceptron model; artificial neural networks; training, inference, software, programming; vector matrix multiplications; design vectors of AI system and performance; AI applications. Prerequisites: Undergraduate-level knowledge in electrical and/or computer engineering or computer science. (3 credit hours)

SEAS 6525 Secure & Trustworthy AI: This course seeks to provide students with a thorough understanding of artificial intelligence (AI), Generative AI (GenAI) and Machine Learning (ML), focusing specifically on security, governance, and how to protect sensitive data using AI models. The course is based on a comprehensive and up-to-date handbook. The course is designed to provide AI practitioners, IT professionals, data scientists, security experts, policymakers, and students with the necessary knowledge and tools to securely and responsibly create, implement, and operate AI and ML systems. (3 credit hours)

SEAS 6413 Cloud and Big Data Management: Topics related to big data and cloud computing, including data centers, virtualization, hardware and software architecture, as well as system-level issues on performance, energy efficiency, reliability, scalability and security. (3 credit hours)

SEAS 6414 Python Applications in Data Analytics: Introduction to programming with Python with applications in Data Analytics including automating data cleaning, machine learning, text mining, time series analysis, anomaly detection, DoS attack detection, and spam detection. (3 credit hours)

SEAS 6505 Quantitative Foundations in AI: Essential math concepts for AI. Probability & statistics fundamentals. Linear algebra principles. Optimization techniques. Algorithm development foundations. Analytical skills for AI. Technical prowess in AI. AI algorithm analysis. (3 credit hours)

SEAS 6510 Natural Language Processing with Deep Learning: Deep Learning for NLP. Recurrent Neural Networks (RNNs). Long Short-Term Memory (LSTM). Transformers in NLP. Text classification, sentiment analysis, and prompt engineering. Large Language Model. Attention mechanisms. Word embeddings & representation. (3 credit hours)

SEAS 6515 Introduction to Computer Vision: Fundamentals of computer vision. Image processing techniques. Feature extraction methods. Object detection and recognition. Deep learning in computer vision. Convolutional Neural Networks (CNNs). Practical computer vision applications. (3 credit hours)

SEAS 6520 Autonomous Systems & Robotics: Delves into the cutting-edge field of intelligent automation, exploring the design, development, and deployment of autonomous systems. Students engage in advanced studies on robotic systems, artificial intelligence algorithms, and sensor integration. (3 credit hours)

SEAS 6599 AI Capstone Project: Propose on a comprehensive AI project, applying acquired skills and knowledge from the program. Tackle real-world problems, design and implement effective solutions under faculty guidance. Demonstrate mastery in AI through project completion and presentation. (3 credit hours)

SEAS 8550 Artificial Intelligence: Law & Ethics: Survey of important law and ethical developments affecting AI in various areas from copyright and other intellectual property, contracts, torts and other laws.   Attention given to both US, EU and other international law recent developments.   Analysis of the various ethical issues and standards that arise from AI and large language models, including intrinsic bias and the significance of training model selection.  (3 credit hours)

Academic Calendar

Session	Dates	Application Deadlines
Summer 2026	week of 6/1/26 – week of 6/29/26	5/16/2026
Fall-1 2026	week of 8/31/26 – week of 10/19/26	8/15/2026
Fall-2 2026	week of 10/26/26 – week of 12/14/26	10/15/2026
Spring-1 2027	week of 1/11/27 – week of 3/16/27	12/7/2026
Spring-2 2027	week of 3/22/27 – week of 5/10/27	3/1/2027

The course order is determined by academic advisors based on student progress. Course details are provided through Blackboard approximately one month before classes begin.

What Can You Do With a Master's in Artificial Intelligence?

Graduates of the online Master’s Degree in Artificial Intelligence are prepared for advanced professional roles focused on developing, deploying, and evaluating AI- and machine-learning–driven systems across technical and organizational environments. The degree supports career advancement for professionals seeking deeper specialization, increased responsibility, and opportunities to contribute to the design and application of intelligent technologies.

Admissions Requirements

Who Should Apply

The online Master’s in Artificial Intelligence is designed for applicants with a strong academic background in engineering or related technical disciplines who are prepared for advanced, graduate-level study.

Applicants should meet the following requirements:

• A bachelor’s degree in engineering, computer science, information technology, mathematics, physics, or a closely related field from an accredited institution
• A minimum GPA of 3.0 on a 4.0 scale
• A grade of C or higher in at least one college-level calculus course and one college-level statistics course. (Applicants who do not fully meet the calculus or statistics requirement but are otherwise qualified may be conditionally admitted and required to complete an additional 3-credit course during their first semester.)
• Applicants outside the United States should review international admissions requirements for additional criteria
• Applicants may also apply to a six-course graduate certificate in Artificial Intelligence Engineering; upon successful completion of the certificate and reapplication, all certificate courses may be applied toward the Master’s degree*

*Subject to program policies and academic requirements.

Application Materials

There is no application fee for GW’s online engineering programs.

A complete application includes:

• Resume or CV
• Statement of Purpose (250 words or fewer) outlining academic goals, research interests, and relevant experience
• Official transcripts from all institutions where a degree was earned
• Two letters of recommendation, including at least one professional reference
• GRE scores (optional), which may be submitted if available to strengthen the application

After You Apply

Applicants are expected to remain engaged throughout the admissions process. You will receive email updates as your application is reviewed, and timely responses to requests for materials are required to keep your application moving forward.

Frequently Asked Questions

How does this artificial intelligence program differ from a data science or computer science master’s degree?

This Master’s Degree in Artificial Intelligence focuses on the engineering and deployment of intelligent systems, with emphasis on machine learning, advanced algorithms, and AI-driven technologies. Unlike data science programs that primarily emphasize statistical analysis and data interpretation, or computer science programs with broader theoretical scope, this program centers on building, evaluating, and applying AI and machine learning models in real-world, engineering-focused contexts, while also addressing ethical and societal considerations often explored in a master’s degree in machine learning or related graduate programs.

Do I need an engineering degree to apply?

Applicants should hold a bachelor’s degree in engineering, computer science, or a closely related technical field. Candidates with other quantitative or technical backgrounds may be considered on a case-by-case basis, depending on academic preparation and professional experience.

Do I need an engineering degree to apply?

Applicants should hold a bachelor’s degree in engineering, computer science, or a closely related technical field. Candidates with other quantitative or technical backgrounds may be considered on a case-by-case basis, depending on academic preparation and professional experience.

Is the GRE required?
 

No. The GRE is not required for admission to the online Master’s in Artificial Intelligence.

Can I work full time while enrolled?

Yes. The program is designed for working professionals. Courses are delivered online with one scheduled evening class per week, allowing students to balance coursework with full-time employment.

Are international applicants eligible?

Yes. International applicants are welcome to apply. Additional documentation, including proof of English language proficiency, may be required depending on prior education and background.

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