AINS6200: AI for Marketing & Customer Insights

AINS6200: AI for Marketing & Customer Insights#

Aurnova MSAI track: Business AI
Credits: 3
Format: 8-week online graduate course

Uses AI for segmentation, recommendations, campaign optimization, customer analytics, content workflows, and measurement.

This course uses the Aurnova delivery model: GitHub Pages provides learner readings and slides, the restricted instructor repository contains teaching and grading materials, and each enrolled learner receives one complete private student repository for all eight modules.

Course Outcomes#

By the end of the course, students will be able to:

  • explain the major concepts and tradeoffs in AI for Marketing & Customer Insights;

  • build or evaluate applied AI artifacts aligned with the course domain;

  • document assumptions, evidence, limitations, and operational risks;

  • connect technical work to governance, stakeholder needs, and deployment readiness.

Module Map#

  1. Customer data and segmentation — How does AI identify useful customer groups?

  2. Recommendation systems — How do recommendations balance relevance, diversity, and business goals?

  3. Campaign optimization — How can AI improve experimentation and targeting?

  4. Customer journey analytics — How do signals across channels form a coherent picture?

  5. Generative AI for marketing operations — Where can generation increase throughput without weakening brand control?

  6. Measurement, attribution, and incrementality — What evidence shows marketing impact?

  7. Privacy, consent, and trust — How do marketing AI systems respect customers?

  8. AI customer insights portfolio — What should executives trust and act on?

::{admonition} Your private student workspace :class: tip

This GitHub Pages site is the learner-facing textbook for AINS6200 AI for Marketing and Customer Insights. It intentionally does not link to the restricted instructor repository or to graded exercise files.

For hands-on work, return to the current module in Populi and open the private student repository assigned to you. Clone that repository once, or open its Codespace. To use Colab, choose File → Open notebook → GitHub, authorize your private repositories, and select the lab or exercise from your assigned repository.

Complete the work there, commit and push it, and submit exactly what the Populi assignment requests. Populi remains the official source for due dates, submissions, feedback, and grades.

Start Here#

Choose the path that matches your role:

  • Students: begin with How to Use This Course, review each module’s overview, reading, and slides here, then return to Populi and work in the assigned private student repository.

  • Faculty: begin in the restricted Populi faculty area and instructor repository; teaching notes, grading keys, and reference solutions are intentionally absent from this learner site.

  • Technical setup: use Technical Requirements and Setup. Clone your private student repository once or open its Codespace/Colab notebooks; a paid Colab Pro subscription and dedicated local GPU are not required.

  • Readings: use Authoritative Readings and Resources to connect module claims to primary standards, official documentation, and open textbooks.

  • Student workspace: Populi provides the only authoritative link to each learner’s complete private repository; do not use or request access to a course-source or instructor repository.

What Is Interactive?#

The readings and rendered slides are navigable web pages. Interactive labs and exercises are delivered only through each learner’s private student repository; Populi supplies the official repository link, due date, submission, feedback, and grade. “RISE-ready” means a facilitator can open a slide notebook in JupyterLab for presenter mode; students can read the same deck in the browser without installing RISE.