Artificial Intelligence, MS (Boston)

The Master of Science in Artificial Intelligence provides a comprehensive framework encompassing foundational algorithms, theory, and practical applications in the rapidly evolving field of AI. This program offers students the essential knowledge and skills to design, develop, and implement AI systems across various high-demand sectors. The core curriculum is designed to provide in-depth understanding of fundamental AI concepts, forming a solid foundation for both theoretical and practical aspects of artificial intelligence.

Building on this strong foundation, students can delve into advanced AI applications through interdisciplinary concentrations tailored to industry needs. These concentrations include computer vision, continuous process engineering, machine learning, and robotics and agent-based systems.

The master's in artificial intelligence is an interdisciplinary degree offered by Khoury College of Computer Sciences, the College of Engineering, and Bouvé College of Health Sciences. Descriptions of the concentrations offered in this degree are as follows:

• Bioengineering—College of Engineering

  • Students in the bioengineering concentration seek to develop the knowledge and skills to integrate emerging machine learning approaches with engineering principles to understand and interact with complex biological systems. Coursework focuses on using quantitative and data-driven techniques in the context of medical diagnostics, biological signal processing, drug discovery, personalized medicine, and genomic medicine. Successful graduates are prepared to develop AI-driven engineering approaches toward designing, optimizing, and improving healthcare solutions, pharmaceuticals and innovative medical intervention techniques.

• Computer Vision—College of Engineering

  • The computer vision concentration offers students an opportunity to obtain the knowledge and skills to drive innovation at the intersection of new and emerging vision systems and AI. Through utilizing AI and machine learning solutions for a wide range of applications, the concentration covers image enhancement/restoration, object recognition, navigation, graphics rendering, and pattern classification.

• Continuous Process Engineering—College of Engineering

  • ​The continuous process engineering concentration offers students an opportunity to obtain the knowledge and skills to revolutionize how industrial processes are designed, monitored, and optimized. The program aims to prepare students to utilize AI and machine learning solutions to enhance process efficiency, predictive maintenance, and real-time decision making in industries such as chemicals, pharmaceuticals, and energy. Successful graduates are prepared to integrate AI-driven solutions into continuous manufacturing environments to improve safety, sustainability, and productivity.

• Energy Systems—College of Engineering

  • The energy systems concentration offers students an opportunity to obtain the knowledge and skills to drive innovation in sustainable and intelligent energy systems. Students examine how to utilize AI and machine learning solutions to support smart energy grid operations, integrate renewable energy sources, and create responsive and resilient systems.

• Health Data—Bouvé College of Health Sciences

  • This interdisciplinary concentration is designed to prepare students to tackle pressing challenges at the intersection of artificial intelligence and health. Students work directly with real-world health and wellness data, applying cutting-edge AI techniques to problems that matter. Students integrate technical skills from their core coursework with specialized health data expertise, gaining versatility to work across the entire health ecosystem, from clinical settings to public health to digital health startups. Whether building prototype AI-driven health interventions or uncovering insights from complex datasets, students engage with authentic challenges facing the field today. Throughout the concentration, students address critical questions about equitable health technology design and responsible AI deployment in high-stakes healthcare contexts.

• Machine Learning—Khoury College of Computer Sciences

  • The goal of the machine learning concentration is to provide students with practical, hands-on experience in designing, implementing, and optimizing machine learning models for real-world applications. The curriculum positions graduates to pursue roles that leverage AI to drive innovation and efficiency in a wide variety of industries and domains.

• Robotics and Agent-Based Systems—Khoury College of Computer Sciences

  • The goal of the robotics and agent-based systems concentration is to provide students with expertise in designing and developing intelligent robotic systems and autonomous agents capable of performing complex tasks in dynamic environments. The curriculum positions graduates to pursue roles that contribute to innovations in automation, human-robot interaction, and intelligent systems design.

• ​Sustainability for Infrastructure and Environment—College of Engineering

  • Offered through the Department of Civil and Environmental Engineering, this concentration is designed to prepare students with the knowledge and skills to create impactful next-generation solutions at the intersection of the natural and built environments. Students are prepared to utilize AI and machine learning solutions to create smarter, healthier cities; to ensure continued and optimized functions of critical infrastructure in the face of a changing climate; and to support closed-loop material management across all sectors.

Students are admitted to the college associated with their concentration, and their degree is awarded by that college. Students follow all policies associated with their college of admission. 

Complete all courses and requirements listed below unless otherwise indicated.

Core Requirements

A cumulative GPA of 3.000 or higher is required in the following:

Course List

Code	Title	Hours
CS 5100	Foundations of Artificial Intelligence	4
CS 5130 and CS 5131	Applied Programming and Data Processing for AI and Recitation for CS 5130	4
DADS 5200	Mathematics for Machine Learning	4
or DS 5020	Introduction to Linear Algebra and Probability for Data Science
EECE 5644	Introduction to Machine Learning and Pattern Recognition	4
or DADS 7275	Machine Learning and Data Analytics

Concentrations

Complete one of the following:

• Bioengineering—College of Engineering
• Computer Vision—College of Engineering
• Continuous Process Engineering—College of Engineering
• Energy Systems—College of Engineering
• Health Data—Bouvé College of Health Sciences
• Machine Learning—Khoury College of Computer Sciences
• Robotics and Agent-Based Systems—Khoury College of Computer Sciences
• Sustainability for Infrastructure and Environment—College of Engineering

Program Credit/GPA Requirements

32 total semester hours required 
Minimum 3.000 GPA required

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Bioengineering Concentration —College of Engineering 

Course List

Code	Title	Hours
Complete 8 semester hours from the following:		8
BIOE 5740	Intermediate Computing Skills for Bioengineers
BIOE 5750	Modeling and Inference in Bioengineering
BIOE 5880	Computational Methods in Systems Bioengineering
Complete 4 semester hours from the following:		4
BIOE 5115	Dynamical Systems in Biological Engineering
BIOE 5860	Engineering Approaches to Precision Medicine I
PHIL 5010	AI Ethics
PHTH 5350 and PHTH 6130	Using SAS in Public Health Research and Public Health Technologies: Ethics and Equity
Capstone
BIOE 5770	Machine Learning Methods in Biology and Health	4

Computer Vision Concentration—College of Engineering

Continuous Process Engineering Concentration—College of Engineering

Course List

Code	Title	Hours
Complete 8 semester hours from the following (students without a chemical engineering degree are advised to choose CHEM 5101 and CHEM 5102, which serve as a bridge from other degrees):		8
CHME 5101 and CHME 5102	Fundamentals of Chemical Engineering: Fluid, Heat, and Mass Transfer and Fundamentals of Chemical Engineering: Thermodynamics and Kinetics
CHME 5510 and CHME 5515	Fundamentals in Process Safety Engineering and Process Safety Engineering for Biotechnology and Pharmaceutical Industries
CHME 7600 and CHME 7601	Pharmaceutical Engineering I and Pharmaceutical Engineering II
Complete 4 semester hours from the following:		4
CHME 5137	Computational Modeling in Chemical Engineering
CHME 5520	Designing for Process Safety
CHEM 5641 and CHME 7901	Computational Chemistry and Journal Club in Chemical Engineering
CHME 5649	Numerical Strategies and Data Analytics for Chemical Sciences
IE 7270	Intelligent Manufacturing
PHIL 5010	AI Ethics
PHSC 5900	AI in Drug Discovery and Development
Capstone
CHME 6580	Artificial Intelligence for Process Engineering Capstone	4

Energy Systems Concentration—College of Engineering

Course List

Code	Title	Hours
Complete 12 semester hours from the following:		12
CHME 5621	Electrochemical Engineering
CHME 5692	Carbon Capture, Utilization, and Storage
ENSY 5000	Fundamentals of Energy System Integration
ENSY 5700	Renewable Energy Development
ENSY 5800	Applications of Artificial Intelligence in Energy Systems
MATL 6270	Principles, Devices, and Materials for Energy Storage and Energy Harvesting
ME 5374	Special Topics in Mechanical Engineering
ME 6200	Mathematical Methods for Mechanical Engineers 1
PHIL 5010	AI Ethics
Capstone
ME 7945	Master’s Project	4

Health Data Concentration—Bouvé College of Health Sciences

Course List

Code	Title	Hours
HLTH 5810	Survey of Health-Related Data	4
HLTH 5820	AI Project for Health Applications	4
Complete one of the following two options:		8
Option 1: Capstone or Project
Complete 4 semester hours from the following:
HINF 5300	Personal Health Interface Design and Development
HINF 5500	Artificial Intelligence and Health Informatics
HLTH 5550	Product Design, Development, and Innovation in Health Science
NNMD 5310	Bioethics in the Age of Artificial Intelligence
PHIL 5010	AI Ethics
PHSC 5905	Artificial Intelligence and Machine Learning in Drug Discovery: Concepts and Applications
PHTH 5320	Grant Writing in Public Health
PHTH 5350	Using SAS in Public Health Research
PHTH 5360	AI at the Intersection of Health and Society
PHTH 6130	Public Health Technologies: Ethics and Equity
Complete one of the following:
HLTH 6980	Capstone
HLTH 7995	Master's Project
Option 2: Thesis
Complete the following course twice at 4 semester hours each:
HLTH 7990	Thesis

Machine Learning Concentration—Khoury College of Computer Sciences

Course List

Code	Title	Hours
CS 5800	Algorithms	4
Complete 8 semester hours from the following:		8
CS 5180	Reinforcement Learning and Sequential Decision Making
CS 5330	Pattern Recognition and Computer Vision
CS 6120	Natural Language Processing
CS 6200	Information Retrieval
CS 6220	Data Mining Techniques
CS 7140	Advanced Machine Learning
CS 7150	Deep Learning
CS 7180	Special Topics in Artificial Intelligence
Capstone
Complete 4 semester hours from the following:		4
CS 6170	AI Capstone
CS 8674	Master’s Project

Robotics and Agent-Based Systems Concentration—Khoury College of Computer Sciences

Course List

Code	Title	Hours
CS 5800	Algorithms	4
Complete 8 semester hours from the following:		8
CS 5180	Reinforcement Learning and Sequential Decision Making
CS 5335	Robotic Science and Systems
EECE 5550	Mobile Robotics
EECE 5554	Robotics Sensing and Navigation
Capstone
Complete 4 semester hours from the following:		4
CS 6170	AI Capstone
CS 8674	Master’s Project

Sustainability for Infrastructure and Environment Concentration—College of Engineering

Course List

Code	Title	Hours
Complete 8 semester hours from the following, including at least 4 semester hours from Applied AI in Urban/Environmental Systems.		8
Applied AI in Urban/Environmental Systems
CIVE 7100	Time Series and Geospatial Data Sciences
CIVE 7150	Data-Driven Decision Support for Civil and Environmental Engineering
CIVE 7151	Urban Informatics and Processing
Advanced AI/ML Concepts
CS 6120	Natural Language Processing
EECE 5614	Reinforcement Learning and Decision Making Under Uncertainty
EECE 7397	Advanced Machine Learning
IE 7615	Deep Learning for AI
Applications to the Discipline
Complete 4 semester hours from the following:		4
CIVE 5275	Life Cycle Assessment of Materials, Products, and Infrastructure
CIVE 5280	Remote Sensing of the Environment
CIVE 5281	Coastal Dynamics and Design
CIVE 5373	Transportation Systems: Analysis and Planning
CIVE 5524	Vibration-Based Structural Health Monitoring
CIVE 7155	Dynamics and Control of Infrastructure Systems
CIVE 7341	Structural Reliability
CIVE 7380	Performance Models and Simulation of Transportation Networks
CIVE 7381	Transportation Demand Forecasting and Model Estimation
Capstone
CIVE 7945	Master’s Project	4

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