Virginia Polytechnic Institute and State University

How this program compares

At an estimated $20.3K in total tuition, the Master’s in Engineering in Machine Learning & Applications sits roughly 52% below the $42.4K average for AI master's programs in our database — placing it in the 28th 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: A bachelor's degree in engineering, computer science, or a related quantitative field with a minimum GPA of 3.0 is required, along with prerequisite coursework in linear algebra, calculus, probability, and programming.

About This Program

This master's degree offers graduate students a strong foundation in machine learning and deep learning, preparing them to solve complex real-world problems in industrial and social contexts. Coursework concentrates on Machine Learning and Deep Learning. Most students complete it in about 1.5 years.

Estimated total tuition is $20.3K, below the $42.4K average for AI master's programs in our database and in the 28th percentile on cost at this level. That makes it one of the more affordable options for students weighing return on investment.

Advance as Machine Learning Engineer in Engineering AI with machine learning expertise Graduates frequently move into roles such as Machine Learning Engineer, with reported salaries around $120,000.

Career Outcomes

Advance as Machine Learning Engineer in Engineering AI with machine learning expertise

• 1. Machine Learning Engineer
• 2. AI Systems Engineer
• 3. Data Scientist
• 4. ML Applications Specialist

What You'll Learn

• Design and implement machine learning models for engineering problems
• Apply deep learning techniques to real-world data
• Optimize algorithms for scalable ML systems
• Develop applications integrating ML with engineering domains

Curriculum Highlights

The structure includes at least four concentration courses in software and machine intelligence, plus a required capstone project and ethics training.

Top Employers

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

Admissions

A bachelor's degree in engineering, computer science, or a related quantitative field with a minimum GPA of 3.0 is required, along with prerequisite coursework in linear algebra, calculus, probability, and programming.

Application Materials

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

Academic Requirements

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