Worcester Polytechnic Institute

What you'll study

The programme builds a foundation in computer science, mathematics and statistics before moving into focused AI topics. Early years cover programming, data structures and algorithms, discrete mathematics, calculus, linear algebra, probability and statistics. Core AI and advanced computing topics include machine learning, deep learning, natural language processing, computer vision, reinforcement learning, robotics, databases and software engineering.

WPI’s curriculum emphasises experiential learning: students take laboratory courses, project-based classes and design studios. Two signature projects punctuate the degree — a collaborative problem-focused project with social or global context and a major qualifying project (capstone) in the final year where students design and deploy an AI solution. Electives and technical electives allow specialisation in areas such as autonomous systems, human-centred AI, ethical and legal aspects of AI, cloud-scale systems, and applied data science.

• Foundations: programming, data structures, algorithms
• Mathematical tools: calculus, linear algebra, probability & statistics
• Core AI: supervised/unsupervised learning, deep learning, NLP, computer vision
• Systems: databases, distributed systems, software engineering
• Applications: robotics, autonomous systems, human–computer interaction
• Capstone and projects: team-based IQP-style projects and Major Qualifying Project

Entry requirements

Applicants should have a strong high-school background in mathematics (including calculus) and science, and experience in programming is highly desirable. Typical academic preparation includes courses in algebra, geometry, pre-calculus or calculus, physics and a programming course or self-directed coding experience. Admissions decisions consider the whole applicant profile including transcripts, recommendations and evidence of project work or extracurricular activities related to computing or engineering.

International applicants must demonstrate English proficiency according to university policy. Students without prior college-level computing coursework may be admitted but should expect to take preparatory courses in programming and discrete mathematics during the first year.

Career prospects

Graduates are prepared for technical roles that require strong software and quantitative skills. Common entry-level positions include machine learning engineer, data scientist, AI software developer, computer vision or NLP engineer, robotics or autonomous systems engineer, and software engineer roles with an emphasis on analytics or intelligent systems. The programme also lays groundwork for graduate study in AI, computer science, robotics or related fields.

WPI’s emphasis on team projects, industry collaborations and applied research helps students build a portfolio of deployed systems and research outcomes, which employers value for roles in technology companies, startups, research labs, healthcare, automotive and manufacturing sectors, and public-sector organisations.

Why study at Worcester Polytechnic Institute

WPI is known for a project-based curriculum that integrates classroom learning with hands-on, team-oriented problem solving. The institute’s model requires substantial project work and provides opportunities to apply AI methods to real-world problems through interdisciplinary teams, industry-sponsored projects and research centres. Students benefit from access to well-equipped labs, faculty research in AI and robotics, and strong ties with industry partners and regional tech employers.

Small class sizes and an emphasis on undergraduate research make it easier for students to work closely with faculty on specialised topics. The programme’s practical focus, combined with WPI’s global project experiences, prepares graduates to move quickly into technical roles or to continue into specialised graduate study.