Program Overview
The Master of Artificial Intelligence provides advanced training in cutting-edge AI research, deep learning architectures, advanced natural language processing, and AI system optimization. Students develop expertise in theoretical foundations of machine learning, research methodologies, and advanced implementation techniques. The program emphasizes innovation, research contribution, strategic AI deployment, and leadership in AI projects, preparing graduates for senior AI engineering roles, research positions, AI leadership, or doctoral studies in artificial intelligence.
To develop AI leaders and researchers who can advance the field through innovation, conduct rigorous AI research, architect enterprise-scale AI solutions, and drive organizational AI strategy while maintaining ethical standards and global perspective.
- Total Credit Hours: 36
- Core Courses: 24 credit hours
- Concentration/Electives: 9 credit hours
- Capstone/Thesis: 3 credit hours
- Delivery: 100% Online with research mentorship
- Duration: 12-24 months
- Format: Asynchronous with advanced research projects
Program Educational Objectives
Within 3-5 years of graduation, MAI graduates will:
- Hold senior positions as AI researchers, principal engineers, or AI architects
- Lead complex AI research and development initiatives
- Architect and deploy enterprise-scale AI systems
- Drive AI strategy and innovation in organizations
- Mentor junior AI professionals and lead technical teams
- Pursue doctoral education or become recognized AI thought leaders
- Contribute to advancing state-of-the-art in AI through research and innovation
Program Curriculum
Course Code | Course Title | Credit Hours |
Core Courses (24 Credit Hours) | ||
MAI 601 | Advanced Machine Learning Theory | 3 |
MAI 610 | Deep Learning Architectures and Optimization | 3 |
MAI 620 | Advanced Natural Language Processing | 3 |
MAI 630 | Advanced Computer Vision and 3D Vision | 3 |
MAI 640 | Advanced Reinforcement Learning | 3 |
MAI 650 | AI Research Methodologies | 3 |
MAI 660 | Probabilistic Graphical Models | 3 |
MAI 670 | AI System Architecture and Scalability | 3 |
Concentration/Electives (9 Credit Hours) | ||
MAI 710 | Multimodal AI and Foundation Models | 3 |
MAI 720 | AI for Scientific Discovery | 3 |
MAI 730 | Neuro-Symbolic AI | 3 |
Capstone/Thesis (3 Credit Hours) | ||
MAI 799 | AI Research Thesis | 3 |
Student Learning Outcomes
Upon completion of the Master of Artificial Intelligence, graduates will be able to:
- Conduct independent AI research contributing novel insights to the field
- Design and implement state-of-the-art deep learning architectures
- Develop advanced NLP systems using transformer models and large language models
- Create sophisticated computer vision solutions including 3D vision and video understanding
- Implement and optimize reinforcement learning for complex decision-making tasks
- Architect scalable AI systems for enterprise deployment
- Evaluate and advance theoretical foundations of machine learning algorithms
- Publish research findings in peer-reviewed venues
- Lead AI projects and mentor technical teams
- Drive AI innovation and strategic initiatives in organizations
Career Opportunities
Graduates of the Master of Artificial Intelligence program may pursue positions including:
- Senior Machine Learning Engineer
- AI Research Scientist
- Principal AI Engineer
- AI Architect
- Deep Learning Research Engineer
- AI Technical Lead
- AI Strategy Consultant
- Computer Vision Research Scientist
- NLP Research Scientist
- AI Product Director
- Research and Development Manager (AI)
- AI Innovation Leader
