George Washington University

How this program compares

At an estimated $36K in total tuition, the Online Master of Engineering in AI & ML sits roughly 15% below the $42.4K average for AI master's programs in our database — placing it in the 55th percentile on cost among the 531 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: Applicants typically need a bachelor's degree in a STEM field or related discipline with a strong academic record. Professional experience in technology, engineering, or data science is preferred but not always required; international applicants must demonstrate English proficiency via TOEFL (80+ iBT) or equivalent.

About This Program

This STEM-designated online degree provides students with deep expertise in advanced machine learning tasks and AI system design. Coursework concentrates on Natural Language Processing (NLP) and Deep Learning. Most students complete it in about 1 year.

Estimated total tuition is $36K, below the $42.4K average for AI master's programs in our database and in the 55th percentile on cost at this level. That puts it in the mid-range on price among comparable programs.

Advance as Machine Learning Engineer in Engineering AI with natural language processing (nlp) expertise Graduates frequently move into roles such as Machine Learning Engineer, with reported salaries around $135,000.

Career Outcomes

Advance as Machine Learning Engineer in Engineering AI with natural language processing (nlp) expertise

• 1. Machine Learning Engineer
• 2. AI Systems Architect
• 3. Data Scientist
• 4. AI Research Engineer

What You'll Learn

• Design, implement, and optimize machine learning models for real-world engineering problems
• Apply advanced AI techniques including deep learning, reinforcement learning, and natural language processing
• Engineer data pipelines and systems that support large-scale AI applications
• Evaluate the societal impacts and ethical implications of AI/ML technologies in professional contexts

Curriculum Highlights

The curriculum emphasizes applied machine learning, cloud systems, and robotics, requiring 30 credits for completion including a mentored capstone.

Top Employers

Top employers include Google, Microsoft, Amazon, IBM, Meta, OpenAI, and major financial institutions and government agencies investing in AI infrastructure and applications.

Admissions

Applicants typically need a bachelor's degree in a STEM field or related discipline with a strong academic record. Professional experience in technology, engineering, or data science is preferred but not always required; international applicants must demonstrate English proficiency via TOEFL (80+ iBT) or equivalent.

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 2–3
• Resume: Required
• Official Transcripts: Required

Academic Requirements

• Degree Required: Master of Engineering (MEng)
• GRE/GMAT: Not Required
• TOEFL/IELTS: Required for international students (TOEFL 80+ iBT / IELTS 6.5+)