Programs Catalog

Licensable offerings for institutional launch.

Review programs by audience, delivery format, and implementation load. Each listing is designed to support a buyer conversation with enough detail for academic and operational review.

36-credit online master's degree 100% online

MSAI

A complete Master of Science in Artificial Intelligence curriculum designed for institutional launch, including a 27-credit core, 9-credit specialization tracks, and a culminating capstone.

Audience
Universities, graduate divisions, and adult-serving online programs
Credits
36 total credits
Duration
36 credit hours across core plus specialization study
Implementation
Degree-ready curriculum with core, specializations, and capstone

What institutions get

  • Launch a full graduate AI degree with an academically coherent core sequence.
  • Offer differentiated specialization pathways in healthcare, business, or cybersecurity AI.
  • Support workforce-relevant outcomes with technical, ethical, and project-based training.

Curriculum highlights

  • AINS6001 Foundations of Artificial Intelligence
  • AINS6002 Machine Learning & Predictive Modeling
  • AINS6003 Deep Learning & Neural Networks
  • AINS6004 Natural Language Processing
  • AINS6005 AI Ethics, Law & Policy
  • AINS6006 Big Data Management for AI Applications
  • AINS6007 Applied AI Programming with Python
  • AINS6008 AI Project Management & Deployment
  • AINS6009 Capstone Project
  • AINS6010 Local AI & Deployment to Hardware certificate course

Specialization tracks

Healthcare AI

  • AINS6100 AI in Medical Imaging
  • AINS6101 Predictive Analytics in Population Health
  • AINS6102 AI for Clinical Decision Support

Business AI

  • AINS6200 AI for Marketing & Customer Insights
  • AINS6201 Automation & Process Optimization
  • AINS6202 AI Strategy for Executives

Cybersecurity AI

  • AINS6300 AI in Threat Detection
  • AINS6301 Automated Response Systems
  • AINS6302 AI for Risk Assessment

Best fit

  • Universities building new AI graduate offerings
  • Colleges expanding online and professional master’s portfolios
  • Institutions seeking fast program launch without writing curriculum from scratch
Certificate course Online with practical deployment labs

Local AI & Deployment to Hardware

A focused course on running AI models on edge devices, on-premises servers, and embedded systems for institutions that want practical, non-cloud AI deployment training.

Audience
Institutions building edge AI, applied AI, or hardware-facing certificates
Credits
Certificate portfolio course
Duration
Single-course certificate or stackable module
Implementation
Certificate-ready applied technical course

What institutions get

  • Teach students to optimize and deploy models under hardware constraints.
  • Expand an AI program with edge, embedded, and local inference capability.
  • Package as a standalone certificate module or elective inside a larger AI program.

Best fit

  • Applied AI and engineering programs
  • Cyber-physical systems curricula
  • Certificate portfolios for workforce and technical learners
Graduate-level AI foundations (5000-level); AIMA textbook sequence emphasizing AI methods for problem solving—search, planning, knowledge, learning, and intelligent agents Online-first; GitHub Classroom + Codespaces; PDF and hosted slides; IMS Common Cartridge (LMS import) for every delivery path

AIMA 5001 — AIMA (Using AI to Make AI)

A complete, licensable deployment of Artificial Intelligence: A Modern Approach at graduate rigor (AIMA 5001): AI-generated slide decks, assignments, autograding hooks, and optional teaching-assistant stack. Each row below is a distinct AIMA5001 course product—demo pages are generated from MyST Markdown in web/myst-sources/ain2001/ (one file per variant, one shared myst build). Same syllabus spine, different delivery and tooling; every variant includes the same IMS Common Cartridge for LMS import where applicable.

Audience
Graduate CS and AI programs adopting Russell & Norvig with modern GitHub, Classroom, and AI-assisted workflows
Credits
Institution-defined (typically 3–4 graduate credits)
Duration
8 weeks sample · 24 Reveal lectures (expandable)
Implementation
Full course repo with Reveal slides, sample PDF slide packs, IMSCC-ready bundles for Canvas/Moodle-style import, GitHub Pages, SAMWISE curriculum tooling, and BEATRICE (AI TA) integration

What institutions get

  • Ship a turnkey AIMA-aligned course with slides, readings, and assignments in one repository.
  • Offer students GitHub Classroom assignments with Codespaces and automated feedback.
  • Layer dialogic (instructor-led Q&A) slide delivery, SAMWISE curriculum server workflows, and BEATRICE for structured AI teaching assistance.

Curriculum highlights

  • Six licensable course products for AIMA 5001 (MyST sources in myst-sources/ain2001/*.md): Basic, AI Delivery, Classroom, Dialogic, SAMWISE, BEATRICE
  • 24 lecture tracks mapped to AIMA 4e with Reveal.js delivery
  • 556+ indexed exercises with autograding and AI-rubric pathways (see course analysis docs)
  • GitHub Classroom templates with devcontainer / Codespaces for assignments
  • Instructor notes system for human and AI teaching assistants (BEATRICE)

Best fit

  • Graduate CS programs adding a rigorous AI foundations course
  • Institutions standardizing on Git + AI tools for programming-heavy courses
  • Teams that want buyer-visible demos for each delivery format before licensing

Common buying structures

The curriculum can be sold in multiple academic formats depending on your institution's program strategy and launch timeline.

Full MSAI program launch

Best for institutions that want a complete graduate AI degree with built-in specialization pathways.

Certificate portfolio

Best for institutions that want stackable AI certificates drawn from the core and Local AI course set.

Specialization-first pilot

Best for teams starting with a healthcare, business, or cybersecurity AI concentration before full rollout.