Full curriculum in prose

Mag.AI-Marketing runs eighteen courses across three terms. The arc moves from audience and message worlds you can simulate before you scale spend, through campaigns, experiments, attribution, and growth loops, to competition, budgets, governed automation, ethics, and a capstone thesis you can defend with evidence. Work is artifact-driven: inspectable models, documented runs, and clear lineage — not slide-only “AI awareness.” Delivery centers on iNQspace (notebooks, simulations, artifacts) and, where courses require it, MCP-scoped connections to real marketing systems. For required artifacts, prerequisites, and AI systems per course, see the authoritative Full curriculum.

Term I — Audience & message worlds¶

Term I formalizes attention, trust, and message dynamics as worlds you can perturb. The goal is honest mechanics — emergence from rules, not personas on posters — so later terms can talk about campaigns and budgets without fooling yourself.

AINS-M6001 — Personal attention & influence systems¶

You treat your own attention, credibility, and message–audience fit as the smallest complete marketing system: stocks and flows, time allocation, content economics, and how you signal before you model anyone else. The course sets the template for executable worlds and reflection (SAMWISE) that the rest of the program reuses.

AINS-M6002 — Audience worlds¶

You build populations of agents with heterogeneous habits, trust thresholds, and decision rules. Segmentation and churn-like behavior emerge from mechanics; you calibrate models to qualitative evidence or documented priors and record where the world disagrees with reality.

AINS-M6003 — Positioning & narrative systems¶

You model positioning and story as mechanisms: categories, promises, proof, and narrative arcs that change audience state over time. Positioning is constraints and feedback, not a slogan — so claims stay testable inside the world you already built.

AINS-M6004 — Brand as dynamic system¶

You treat brand as state: awareness, association, trust, elasticity — drifting with experience, creative fatigue, and shocks. Brand is dynamic, not a style guide; you stress scenarios (refresh, scandal, competitor moves) in the same simulation spirit as earlier courses.

AINS-M6005 — Channel & content economics¶

You implement reach, cost, and conversion across channels and content types: saturation, creative throughput, and unit economics. Meta-, Google-, and Amazon-class surfaces appear as parallel modules — same ontology, different auctions and reporting — so “tooling” means modeled constraints, not trivia.

AINS-M6006 — Measurement, privacy & compliance¶

You fold measurement, consent, and platform policy into the world as rules: what can be observed, what is inferred, what is forbidden. GDPR/CCPA-style ideas and major platform policies become first-class constraints, preparing Term II’s campaign and attribution work for defensibility, not vibes.

Term II — Campaign & growth worlds¶

Term II simulates campaigns, experiments, attribution, partnerships, loops, and crises as coordinated dynamics with delays, budgets, and honest failure modes — still tied to the worlds you built in Term I.

AINS-M6101 — Campaign orchestration¶

You model multi-touch campaigns: frequency, sequencing, rotation, pacing, and coordination across touchpoints. Scenarios span social, Google, and Amazon (or faculty-approved analogs) so orchestration means cross-ecosystem mechanics, not a single ad set.

AINS-M6102 — Creative testing at scale¶

You build experiment systems: lift, variance, sample size, peeking, and when to stop — treating creative testing as a statistical world. AI-assisted creative enters as disclosed, QA’d experimental factors where relevant.

AINS-M6103 — Data-driven marketing & attribution¶

You implement attribution and decision workflows grounded in data: multi-touch limits, incrementality concepts, triangulation across ecosystem metrics, and retrieval / evaluation discipline for LLM outputs — with privacy hooks and explicit distrust of single dashboards.

AINS-M6104 — Partnerships & ecosystem¶

You model partners, affiliates, and ecosystems as agents with incentives, leakage, and multi-sided dynamics — including B2B co-sell patterns and consumer affiliate mechanics where they matter — so growth isn’t only paid media.

AINS-M6105 — Growth loops & community¶

You model loops and community as reinforced feedback: referrals, UGC, network effects where appropriate, and social and retail reputation (e.g. reviews) as measurable stocks — separating compounding growth from burn.

AINS-M6106 — Crisis & reputation stress tests¶

You adversarially stress reputation: negative virality, misinformation, policy shocks, bad actors. The emphasis is fragility and early warnings — tail risk for brand and community — before strategy and budget work in Term III.

Term III — Strategic marketing worlds¶

Term III moves to competition, policy, allocation, automation, and governance — still grounded in simulatable worlds, but aimed at defense-ready choices and a real deployment story.

AINS-M6201 — Competitive narrative arena¶

You pit world models against each other: competing narratives, offers, and budgets as strategic interaction — differentiation, switching costs, information asymmetry — so “strategy” stays emergent, not a slide deck.

AINS-M6202 — Strategy as marketing policy¶

You encode strategy as policy: rules mapping states to actions under uncertainty (explore/exploit, robustness across scenarios), integrated with the student’s growing world model.

AINS-M6203 — Budget & portfolio allocation¶

You simulate budget allocation across initiatives under liquidity, payback, risk of ruin, and correlated risks — linking spend to brand and growth dynamics without fantasy ROI curves.

AINS-M6204 — Autonomous marketing systems¶

You design self-running marketing subsystems with explicit human-in-the-loop boundaries, monitoring, rollback, and observability for AI steps — automation as governed infrastructure, not a black box.

AINS-M6205 — Ethics, influence & control¶

You formalize alignment and governance for influence systems: stakeholder maps, harms, Goodhart dynamics, and legible oversight — tying governance to components you might actually deploy.

AINS-M6206 — Magisterium thesis (marketing)¶

The capstone: a real system, simulation validation, measurable outcomes, and defense-ready documentation — integrating artifacts and reflection across terms into a Magisterium thesis package.