The graduate certificate in artificial intelligence lets either existing graduate students or working professionals gain exposure to cutting-edge topics in contemporary AI. Available courses cover many AI interest areas, including: Generative language models such as Llama and ChatGPT, Theory and application of machine learning, Robotics and planning. The certificate can be pursued alone, or as part of another graduate degree. All classes are offered in-person only. Students enrolled in the program have access to UNH’s innovative DeepThought AI infrastructure, which provides both inference and fine-tuning access to hosted Llama models, including a retrieval-augmented generation (RAG) infrastructure.
Certificate Requirements
Incoming students must have at least one semester of computer programming or equivalent experience. Some courses require extensive programming background and others require extensive math background. Students interested in the certificate should have at least one of these two possible backgrounds.
Required Courses
- Students complete four courses for the certificate.
- It is recommended that students select one of the pathways outlined below. Or, the certificate may be completed by selecting any four courses from the list of elective courses.
Course List | Code | Title | Credits |
| CS 830 | Introduction to Artificial Intelligence | 4 |
| CS 833 | Mobile Robotics | 4 |
| CS 931 | Planning for Robots | 3 |
| CS 933 | Human Robot Interaction | 3 |
Course List | Code | Title | Credits |
| CS 852 | Foundations of Neural Networks | 4 |
| CS 853 | Information Retrieval and Generation Systems | 4 |
| CS 859A | Natural Language Processing | 4 |
| CS 881 | Data Science for Knowledge Graphs and Text | 4 |
Course List | Code | Title | Credits |
| CS 850 | Machine Learning | 4 |
| CS 852 | Foundations of Neural Networks | 4 |
| CS 857 | Mathematical Optimization for Applications | 4 |
| CS 950 | Advanced Machine Learning | 3 |
Course List | Code | Title | Credits |
| CS 850 | Machine Learning | 4 |
| CS 851A | Reinforcement Learning | 4 |
| CS 852 | Foundations of Neural Networks | 4 |
| CS 959 | Fair, Accountable and Transparent Machine Learning | 3 |
Course List | Code | Title | Credits |
| CS 850 | Machine Learning | 4 |
| CS 851A | Reinforcement Learning | 4 |
| or CS 852 | Foundations of Neural Networks |
| CS 859A | Natural Language Processing | 4 |
| CS 959 | Fair, Accountable and Transparent Machine Learning | 3 |
Course List | Code | Title | Credits |
| CS 850 | Machine Learning | 4 |
| CS 852 | Foundations of Neural Networks | 4 |
| or CS 853 | Information Retrieval and Generation Systems |
| CS 859A | Natural Language Processing | 4 |
| CS 959 | Fair, Accountable and Transparent Machine Learning | 3 |
Course List | Code | Title | Credits |
| 1 | |
| CS 830 | Introduction to Artificial Intelligence | 4 |
| CS 833 | Mobile Robotics | 4 |
| CS 850 | Machine Learning | 4 |
| CS 851A | Reinforcement Learning | 4 |
| CS 852 | Foundations of Neural Networks | 4 |
| CS 853 | Information Retrieval and Generation Systems | 4 |
| CS 855 | Computer Vision | 4 |
| CS 857 | Mathematical Optimization for Applications | 4 |
| CS 859A | Natural Language Processing | 4 |
| CS 881 | Data Science for Knowledge Graphs and Text | 4 |
| CS 931 | Planning for Robots | 3 |
| CS 933 | Human Robot Interaction | 3 |
| CS 950 | Advanced Machine Learning | 3 |
| CS 959 | Fair, Accountable and Transparent Machine Learning | 3 |