Humankind is on the threshold of a new era—an age of artificial intelligence as revolutionary in its global impact as the Industrial Revolution. The Master of Professional Studies in Applied AI program offers working professionals operational immersion and firsthand experiences with an end-to-end AI education that aims to prepare students proactively and thoughtfully for the evolving technology landscape and its challenges. The curriculum focuses on building and implementing AI and machine learning technologies, specializing in conversational AI, machine learning for cybersecurity, 3D imaging, and various electives. This comprehensive approach ensures that students are equipped with the skills and knowledge needed to stay ahead in the rapidly changing field of AI.
For the 2025–2026 academic year, the MPS Applied AI program is being offered as a collaboration between the College of Professional Studies and the Office of the Provost. During this period, students will follow Northeastern University’s Graduate Academic Calendar and be governed by the academic policies and procedures documented in the university’s Graduate Catalog.
During the time a student is designated under the Office of the Provost, the College of Professional Studies will provide each student with full academic and student support services (e.g., academic advising services, co-op and career advising services, International Tutoring Center, etc.).
Beginning in the 2026–2027 academic year, students enrolled in the MPS Applied AI program will transition to the College of Professional Studies, and their official college designation will be updated accordingly in the academic system of record. At that time, students will be governed by the academic policies and procedures documented in the university’s Graduate Catalog, specifically relating to the College of Professional Studies.
Core Courses
Course List | Code | Title | Hours |
| |
| AAI 6600 | Applied Artificial Intelligence | 3 |
| AAI 6610 | Applied Machine Learning | 3 |
| AAI 6620 | Applied Natural Language Processing | 3 |
| AAI 6630 | Applied Computer Vision | 3 |
| 6 |
| Applied Deep Learning | |
| Recommender System | |
| Prompt Engineering | |
| Generative Artificial Intelligence | |
| Applied Reinforcement Learning | |
| Applied Quantum AI | |
| Applied Blockchain AI | |
| AI for Autonomous Systems | |
| Special Research Topics in AI | |
| AAI 6980 | Integrated Experiential Capstone | 4 |
Concentration or Electives Option
A concentration is not required. Students may complete the electives option in lieu of a concentration.
Program Credit/GPA Requirements
34 total semester hours required
Minimum 3.000 GPA required
AI for 3D Imaging Concentration
Course List | Code | Title | Hours |
| |
| AAI 6710 | Graph Signal Processing | 3 |
| AAI 6720 | Graph Neural Networks | 3 |
| AAI 6730 | Deep Learning for 3D Point Cloud Analysis | 3 |
| 3 |
| Applied Deep Learning | |
| Recommender System | |
| Generative Artificial Intelligence | |
| Applied Reinforcement Learning | |
| Applied Quantum AI | |
| Applied Blockchain AI | |
| AI for Autonomous Systems | |
Conversational AI and Chatbots Concentration
Course List | Code | Title | Hours |
| |
| AAI 6660 | Chatbot Architecture | 3 |
| AAI 6670 | Chatbot Application | 3 |
| 6 |
| Applied Deep Learning | |
| Recommender System | |
| Prompt Engineering | |
| Generative Artificial Intelligence | |
| Applied Reinforcement Learning | |
| Applied Quantum AI | |
| Applied Blockchain AI | |
| AI for Autonomous Systems | |
Machine Learning for Cybersecurity Concentration
Course List | Code | Title | Hours |
| |
| AAI 6680 | AI for Cybersecurity | 3 |
| AAI 6690 | Machine Learning for Cyberdetection | 3 |
| 6 |
| Applied Deep Learning | |
| Recommender System | |
| Generative Artificial Intelligence | |
| Applied Reinforcement Learning | |
| Applied Quantum AI | |
| Applied Blockchain AI | |
| AI for Autonomous Systems | |
Electives Option
Course List | Code | Title | Hours |
| |
