Artificial Intelligence Major

Program of Study
Degree Type
Bachelor of Science

Degree Goals and Objectives

To meet the growing demand for expertise in Artificial Intelligence (AI), the Bachelor of Science in Artificial Intelligence (BS-AI) will equip students with a strong foundation in Artificial Intelligence. It will foster their proficiency in computational thinking, mathematics, machine learning, deep learning, natural language processing, human-AI interaction and AI ethics. By providing a comprehensive and adaptable curriculum, we will prepare graduates for successful careers in the AI industry or for graduate school. Students must specialize their degree in an area of interest by selecting one concentration from the list of concentrations offered. The degree balances technical expertise with its application in industry and/or government spaces via an MQP project in Artificial Intelligence. The degree uses real-world experiential learning and research opportunities to ensure students are prepared for a rapidly evolving field and economic landscape so that they are prepared to responsibly lead technological transformation for the benefit of society.

Degree Educational Objectives

In support of its goals and mission, the Artificial Intelligence undergraduate program's educational objectives are to graduate students who will: 

  • Bring together a community of diverse disciplinary backgrounds and experiential perspectives to develop innovative AI-driven solutions to real-world challenges
  • Demonstrate proficiency of AI theory and practice, including machine learning, data science, and systems, to achieve professional excellence
  • Conduct research and project work applying artificial intelligence to tackle the world's challenging problems
  • Engage in discovery through purpose-driven project-based learning
  • Collaborate effectively in teams across disciplines on interdisciplinary initiatives
  • Become leaders in academia, industry and society through comprehensive preparation in AI, data science, computational thinking, mathematics, robotics, communication, and ethics
  • Pursue lifelong learning and continuous professional development to stay at the forefront of this rapidly evolving field
  • Apply AI responsibly with a deep understanding of its societal implications and potential to benefit humanity

Theme

"Model Intelligence, Lead Innovation, Transform Our Future"

Student Outcomes

Students graduating with a Bachelor of Science degree in Artificial Intelligence can:

  • Identify, formulate, and solve complex problems by applying principles from AI and its underpinning disciplines, including from computer science, data science, and mathematical sciences
  • Communicate effectively across disciplines both verbally and in writing
  • Locate, read, and interpret primary literature in Artificial Intelligence
  • Function effectively as members of an interdisciplinary team
  • User their understanding of accepted standards of the ethical and implications of applying AI to solutions in their chosen discipline
  • Acquire and apply new knowledge as needed, using appropriate learning strategies

Degree Distribution Requirements for the Artificial Intelligence Major

Beyond the standard requirements for a BS degree at WPI, the distribution requirements specific for the BS degree in Artificial Intelligence consists of fundamental courses in Computer Science and Mathematical Sciences, core courses in Artificial Intelligence, AI Ethics, Natural or Engineering Sciences, and courses specific to each concentration. BS-AI students must select one and only one concentration.

In total, at least 4/3 units of the courses chosen to meet the degree requirements must be at the 4000-level and above. These 4000-level courses can be satisfied by any aspect of the distribution requirements (core, concentration, etc.).

Computer Science Foundation

Computer science foundation courses must include 2/3 units of introductory computer science (with no more than 1/3 unit at the 1000 level) and 1/3 unit of algorithms.

Minimum Units
3/3

Students who choose the Advanced AI Methods and Technologies Concentration are recommended to take CS 1101/1102 followed by CS 2102/2103 (rather than CS 1004/1005 followed by CS 2119). If a student demonstrates proficiency in a course, they can petition to take an alternate more advanced CS course to fulfill the 3/3 CS foundation requirement. 

Minimum Units
3/3

Mathematical Sciences Foundation

Mathematics foundation courses must include 2/3 units calculus, 3/4 units applied statistics, and 1/3 unit linear algebra.

Minimum Units
4/3

Note: A student must follow standard processes established by the Mathematical Sciences department for appropriate undergraduate course substitutions in Mathematical Sciences. 

Minimum Units
5/3

AI Core Courses

Choose 8/3 units subject to the restrictions below. These include data modeling and access; basics of model-driven approaches, mathematical modeling, prediction, inferencing, AI model pipelines from data extraction to deployment, machine learning, and other core AI subjects. 

Minimum Units
1/3
Minimum Units
1/3

AI Core courses must include at least 2/3 units at the 4000-level or above.

Minimum Units
8/3

Natural or Engineering Science

2/3 units of work chosen in courses with prefixes AE, AREN, BB, BCB, BME, CE, CH, CHE, ECE, ES, GE, ME, NEU, PH, or RBE.

If a course is double counted as meeting this requirement and the concentration or elective disciplinary course requirement from notes 6 or 7 below, then students need to choose more courses from the Distribution Requirements of the BS-AI to meet the 10 units program requirements. 

Minimum Units
2/3

Concentration

6/3 units (6 distinct courses) must be selected from the list of disciplinary courses in one concentration of the BS in AI degree.

Minimum Units
6/3

Disciplinary AI Electives

2/3 units can be chosen from any concentration (not necessarily the student's chosen concentration) or from the AI core courses, as long as the student has met the prerequisites required by the unit offering the course. 

Minimum Units
2/3

Major Qualifying Project (MQP)

Artificial Intelligence MQP projects must apply AI knowledge and techniques within the student's chosen concentration. The MQP can have a sole advisor if the faculty member is core/collaborative AI faculty within the discipline representing the concentration. Otherwise the project will be co-advised by an Ai core/collaborative faculty member, and a second faculty member with disciplinary knowledge.

Minimum Units
3/3
Program Chart and/or Course Flow Chart