Stevens Institute of Technology

How this program compares

At an estimated $57.0K in total tuition, the MS in Machine Learning sits about 34% above the $42.4K average for AI master's programs in our database — placing it in the 74th 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 computer science, mathematics, engineering, or a related quantitative field, with a strong GPA (3.0 or higher). Relevant coursework in programming, linear algebra, and statistics is preferred.

About This Program

A comprehensive graduate program that builds a rigorous foundation in machine learning theory and practical implementation for industry or research careers. Coursework concentrates on Natural Language Processing (NLP) and Machine Learning. Most students complete it in about 1.5 years.

Estimated total tuition is $57.0K, above the $42.4K average for AI master's programs in our database and in the 74th percentile on cost at this level. Applicants should weigh that premium against the program's outcomes and brand.

Excel as Machine Learning Engineer in Cross-Industry AI with natural language processing expertise Graduates frequently move into roles such as Machine Learning Engineer, with reported salaries around $125,000.

Career Outcomes

Excel as Machine Learning Engineer in Cross-Industry AI with natural language processing expertise

• 1. Machine Learning Engineer
• 2. Data Scientist
• 3. AI Research Scientist
• 4. Applied AI Specialist

What You'll Learn

• Design and implement machine learning models using supervised and unsupervised learning techniques[1][2]
• Develop deep neural networks and apply advanced optimization methods to solve complex problems[1]
• Apply machine learning to real-world challenges through capstone projects and industry partnerships[1][2]
• Master mathematical foundations including linear algebra, statistics, and probability for data science applications[1]

Curriculum Highlights

The 30-credit curriculum features courses in mathematical foundations, supervised and unsupervised learning, and advanced electives in computer vision or robotics.

Top Employers

Top employers include Google, Meta, Microsoft, Amazon, OpenAI, and leading financial institutions specializing in quantitative analysis and algorithmic trading.

Admissions

Applicants typically need a bachelor's degree in computer science, mathematics, engineering, or a related quantitative field, with a strong GPA (3.0 or higher). Relevant coursework in programming, linear algebra, and statistics is preferred.

Application Materials

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

Academic Requirements

• Degree Required: Master of Science
• GRE: Required
• TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)