Editorial review · v0.3 · October 26, 2026. Proposed for delivery by the Institute and its qualified instructors, subject to course approval, scheduling and resources. These are model syllabuses, not accredited courses or current enrollment offerings.
Program architecture
Foundations — AI-UG101 →
Applied development — AI-UG301 →
Graduate technical and governance preparation — AI-GR501 + AI-GR601 →
Integrative capstone — AI-GR551.
Pathway is illustrative: prerequisites and credit rules are set by any adopting institution. Each syllabus includes course outcomes, 15 weekly objectives, laboratory/seminar activities, security checkpoints, assessments, reading foundations and capstone evidence.
Program learning outcomes
- Explain AI, machine learning and agentic architectures, limitations and impacts.
- Design and implement reproducible AI applications with defensible engineering decisions.
- Integrate security, privacy, governance and human oversight throughout the lifecycle.
- Evaluate technical performance, reliability, fairness and adversarial robustness.
- Document controls, audit evidence, residual risk and accountable release decisions.
- Communicate and defend technical and ethical trade-offs before peer and governance review.
Curriculum-wide security requirements
SEC-01Identity & access control
SEC-02Privacy & provenance
SEC-03Secure AI design
SEC-04Threat modeling & red teaming
SEC-05Bounded agency & tool security
SEC-06Monitoring & incident response
SEC-07Governance & regulatory accountability
SEC-08Verification & release assurance
Five complete syllabus drafts
01 · Undergraduate · Introductory
AI-UG101
Foundations of Artificial Intelligence
AI history, reasoning, search, ML foundations and safe AI literacy.
15 weeks · Proposed 3 credits · Detailed syllabus
Review complete syllabus →
02 · Undergraduate · Advanced
AI-UG301
Applied AI, Society & Responsible Use
Applied AI, responsible development, explainability, privacy and risk assessment.
15 weeks · Proposed 3 credits · Detailed syllabus
Review complete syllabus →
03 · Graduate · Technical
AI-GR501
Machine Learning & Intelligent Systems
Statistical learning, neural networks, RAG, secure MLOps and evaluation.
15 weeks · Proposed 3 credits · Detailed syllabus
Review complete syllabus →
04 · Graduate · Interdisciplinary
AI-GR601
AI Governance, Security & Moral Reasoning
Risk governance, regulation, controls, moral philosophy and assurance.
15 weeks · Proposed 3 credits · Detailed syllabus
Review complete syllabus →
05 · Graduate · Integrative Capstone
AI-GR551
Agentic AI Systems: Architecture, Secure Development & Deployment
Prompt scripting, tool use, MCP, orchestration, security, hosting and defended release decisions.
15 weeks · Proposed 3 credits · Detailed syllabus
Review complete syllabus →Institute delivery and academic quality
Courses are designed for possible delivery by IAIGCRM faculty, including its founder, through instructor-led seminars, supervised laboratories, project reviews and oral defenses. Before offering any course, the Institute will need to confirm instructors, schedules, learning platform, accessibility accommodations, laboratory infrastructure, licensing, student policies, grading rubrics and any institutional partnership or credit arrangements. Readings and tool versions require verification before adoption.