Applied AI Bachelor of Science

Leading to a Bachelor of Science Degree in Bachelor of Science in Applied AI

The Bachelor of Science in Applied Artificial Intelligence (BSAI) at Wentworth Institute of Technology is an interdisciplinary, career-focused program designed to prepare graduates to apply AI ethically and effectively across diverse industries. BSAI integrates a technical core with application domain-specific pathways in Business Management, Computing, Construction Management, and Life Sciences, with future expansion into Design, Technology, and other growth fields.

 Program Educational Objectives

  • Apply principles of artificial intelligence to develop and deploy AI-driven solutions in real-world settings across industry, government, or nonprofit sectors.
  • Collaborate effectively with interdisciplinary teams, integrating AI techniques with domain-specific knowledge in fields such as business, computing, or the life sciences.
  • Demonstrate awareness of the ethical, legal, and societal implications of AI systems, and contribute to the development of responsible, transparent, and fair AI solutions.
  • Engage in lifelong learning, professional development, or graduate education in AI or related areas.
  • Communicate complex AI concepts, findings, and decisions effectively to both technical and non-technical audiences.

Student Outcomes

  • Analyze a complex problem, and apply principles of computing, data science, and AI to identify and formulate effective solutions.
  • Design, implement, and evaluate an AI-based solution to meet a given set of requirements, informed by domain knowledge in an area of application.
  • Communicate effectively in a variety of professional contexts.
  • Recognize professional responsibilities and make informed judgments in AI practice based on legal and/or ethical principles.
  • Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.

Four-Year Program

Total Required Credits: 120

This is a four-year full-time program, which begins in the fall semester of the student's first year and is planned to end after the summer semester of the student's fourth year. 

Plan of Study Grid
First Year
Fall SemesterCredits
COMP1000 COMPUTER SCIENCE I 4
AAAI1000 Introduction to Applied AI 4
MATH1825 CALCULUS FOR COMPUTING AND AI 4
English Sequence 4
 Credits16
Spring Semester
MATH2825 LINEAR ALGEBRA FOR COMPUTING AND AI 4
MATH2300 DISCRETE MATHEMATICS 4
Domain Elective 1 4
English Sequence 4
 Credits16
Second Year
Fall Semester
COMP3000 APPLICATIONS OF AI 4
PHIL4525 A.I. ETHICS 4
HSS Elective* 4
Free Elective 4
 Credits16
Spring Semester
COMP3125 DATA SCIENCE FUNDAMENTALS 4
Free Elective 4
Domain Elective 1 4
MATH1030 OR MATH2100 Depending on domain requirements 4
COOP2500 INTRODUCTION TO COOPERATIVE EDUCATION 0
 Credits16
Summer Semester
OPTIONAL COOP EDUCATION  
 Credits0
Third Year
Fall Semester
COMP3001 4
CSAS4000 RESPONSIBLE APPLICATIONS OF GENERATIVE ARTIFICIAL INTELLIGENCE 4
Domain Elective 1 4
Free Elective 4
 Credits16
Spring Semester
COOP3500 COOP EDUCATION 1 0
 Credits0
Summer Semester
DATA3333 PRACTICAL DEEP LEARNING 4
Domain Elective 1 4
HSS Elective* 4
Science Elective 4
 Credits16
Fourth Year
Fall Semester
COOP4500 COOP EDUCATION 2 (THIS MAY BE SWITCHED WITH ANOTHER SEMESTER) 0
 Credits0
Spring Semester
COMP4726 APPLIED LARGE LANGUAGE MODELS 4
HSS Elective* 4
Domain Elective 1 4
 Credits12
Summer Semester
AAAI5500 Senior Design 4
Domain Elective 1 4
Domain Elective 1 4
 Credits12
 Total Credits120

ENGL/HSS Note

Students are required to complete:

  • At least one course in Humanities: CSAS, HSSI, HIST, HUMN, LITR and PHIL
  • At least one course in the Social Sciences: CSAS, HSSI, COMM, ECON, ENVM, POLS, PSYC and SOCL
  • The remaining course from either the Humanities or Social Sciences category. 

Students with a three English course sequence may use the third English course to satisfy a Humanities requirement.

A minimum of 20 credits total, including English, humanities, and social science credit, is required to complete the humanities and social sciences graduation requirement.

At least one of the HSS electives must be an Ethics course.

Math Placement may alter the course schedule above. 

Science Electives

Course Title Credits
BIOL1100CELL & MOLECULAR BIOLOGY4
BIOL1700ANATOMY & PHYSIOLOGY I4
BIOL2200ADVANCED MOLECULAR BIOLOGY4
BIOL3000APPLICATIONS IN GENETICS4
CHEM1100GENERAL CHEMISTRY I4
CHEM1600GENERAL CHEMISTRY II4
PHYS1250ENGINEERING PHYSICS I4
PHYS1750ENGINEERING PHYSICS II4
PHYS2000INTRODUCTION TO ASTRONOMY4
PHYS3100MODERN PHYSICS4
The following courses require School approval to satisfy the Science Elective requirement
BIOL2990INDEPENDENT STUDY IN BIOLOGY4
BIOL3800SPECIAL TOPICS IN BIOLOGY4
CHEM2990INDEPENDENT STUDY IN CHEMISTRY4
CHEM3800SPECIAL TOPICS IN CHEMISTRY4
PHYS2990INDEPENDENT STUDY IN PHYSICS4
PHYS3800SPECIAL TOPICS IN PHYSICS4

Domain Electives

Students will choose one of several application domains to contextualize their AI education. These domains include both foundational and advanced coursework from a partner discipline, allowing students to apply AI techniques to domain-specific challenges.

A total of 28 semester credit hours of domain electives must be taken as part of the program. Eight of those credits must be STEM courses. Students declare their chosen domain by the end of their first term.

It currently offers the following domains:

  • Business Management:
  • Computing
  • Construction Management
  • Life Sciences

 Their curriculum structure and course list are shown below.

Business Management Domain

Students complete a minimum of 28 credits:

  • MGMT1000–Introduction to Management (required).

  • At least 8 credits of STEM-designated courses from the following list, such as Decision Analysis, Systems Analysis, or Cybersecurity. 

Course Title Credits
MGMT1025COMPUTER BUSINESS APPLICATIONS4
MGMT1500DECISION ANALYSIS FOR BUSINESS4
MGMT2525SYSTEMS ANALYSIS, DESIGN, AND IMPLEMENTATION4
MGMT2560CYBERSECURITY LAW AND POLICY3
MGMT2650CYBERSECURITY PLANNING3
MGMT2800CYBERSECURITY MANAGEMENT4
MGMT2000MANAGEMENT INFORMATION SYSTEMS4
MGMT2175INTRODUCTION TO SUPPLY CHAINS4
MGMT3250MANAGERIAL ACCOUNTING4
MGMT2550APPLIED PROJECT MANAGEMENT4
 
  • Remaining credits can come from either the list above or the list below.

Course Title Credits
MGMT2750INTEGRATIVE FINANCIAL ACCOUNTING4
MGMT2100MANAGEMENT COMMUNICATIONS4
MGMT2850PRINCIPLES OF MARKETING4
MGMT3650BUSINESS LAW4
MGMT3700HUMAN RESOURCES & LABOR MANAGEMENT3
MGMT3900OPERATIONS MANAGEMENT4
MGMT4400BUSINESS NEGOTIATION PRINCIPLES3
MGMT3225GLOBAL BUSINESS4
MGMT3070TECHNOLOGY ACQUISITION PROJECTS4
MGMT3160PROJECT RISK4
MGMT3550ENTREPRENEURIAL FINANCE4
MGMT3575ENTREPRENEURIAL MINDSET4
MGMT4225ENTREPRENEURIAL LEADERSHIP4
MGMT3080MARKETING FOR ENTREPRENEURS4
MGMT2150CORPORATE FINANCE4
MGMT2350FINANCIAL INSTITUTIONS AND MARKETS4
MGMT4200INVESTMENTS4
MGMT3150INTRODUCTION TO ENTERPRISE RESOURCE PLANNING4
MGMT3165INTRODUCTION TO LEAN SIX SIGMA4
MGMT4275SUPPLY CHAIN LOGISTICS AND PLANNING4

Elective choices enable students to focus on areas such as data-informed decision-making, enterprise systems, finance, operations, supply chain management, or marketing. Technical fluency is developed through the Applied AI core, enabling students to apply AI tools within business contexts.

Computing Domain

The Computing domain provides students with strong foundations in computer science and modern AI techniques. The curriculum emphasizes data structures, algorithms, probability theory, and both classical and contemporary machine learning methods.

While students may fulfill their statistics requirement through either MATH 1030 or MATH 2100 in the shared core, those pursuing the Computing domain are expected to take MATH 2100 to ensure adequate preparation in probability and statistics. Students complete 28 credits of computing-related coursework, including:

Course Title Credits
COMP1050COMPUTER SCIENCE II4
COMP2000DATA STRUCTURES4
COMP2350ALGORITHMS4
COMP4700FOUNDATIONS OF CLASSICAL AI4
or COMP5700
MATH4050MACHINE LEARNING4
COMP/DATA/MATH Elective4
COMP/DATA/MATH Elective4

This sequence integrates theoretical foundations with practical experience in designing, implementing, and evaluating AI systems. Students gain the computational thinking and analytical skills necessary to build reliable and scalable AI solutions.

Construction Management Domain

Students in the Construction Management domain complete the following courses alongside the Applied AI core. These courses provide a foundation in building construction, BIM (Building Information Modeling), plan reading, estimating, project management, and project scheduling. The curriculum emphasizes the full construction lifecycle, from design to delivery, while integrating emerging AI-driven tools such as computer vision for site monitoring, large language models for document analysis, and IoT sensors for safety and efficiency.

A minimum of 28 credits must be completed in this domain, including two Construction Management electives. Electives may be chosen from any CONM course offerings.

Course Title Credits
CONM1200BUILDING CONSTRUCTION4
CONM1525INTRODUCTION TO BUILDING INFORMATION MODELING (BIM)2
CONM1550 INTRODUCTION TO PLAN READING & SPECIFICATIONS2
CONM2200ESTIMATING4
CONM3100CONSTRUCTION PROJECT MANAGEMENT4
CONM3201CONSTRUCTION PROJECT SCHEDULING (CONM Elective)4
CONM4825ARTIFICIAL INTELLIGENCE IN CONSTRUCTION4
CONM Elective4
 

Life Sciences Domain

The Life Sciences domain prepares students to apply artificial intelligence and data science methods to problems in biology, biotechnology, and medicine. Students gain foundational knowledge in cellular and molecular biology, chemistry, and genetics, while developing computational skills for analyzing biological data and simulating complex systems.

Students complete the 32 credits of STEM-designated courses listed below and need not take another Science course, and can count that requirement as fulfilled. 

Course Title Credits
BIOL1100CELL & MOLECULAR BIOLOGY4
BIOL2200ADVANCED MOLECULAR BIOLOGY4
CHEM1100GENERAL CHEMISTRY I4
CHEM1600GENERAL CHEMISTRY II4
CHEM2000BASICS OF ORGANIC & BIOCHEMISTRY4
BIOE2100BIOSTATISTICS FOR BIOENGINEERS4
BIOE3500GENETICS AND TRANSGENICS4
BIOE4400SYNTHETIC BIOLOGY4