Course

AI Marketing & Generative AI Strategies

Faculty
Commerce & Business Administration
Department
Marketing
Course code
MARK 3890
Credits
3.00
Semester length
15 Weeks
Max class size
35
Method(s) of instruction
Lecture
Seminar
Course designation
None
Industry designation
None
Typically offered
To be determined

Overview

Course description
Artificial intelligence is transforming digital marketing, and professionals who can integrate AI-driven strategies will gain a competitive edge. This course introduces students to AI applications in marketing, covering data-driven decision-making, content generation, and campaign automation. Through applied learning, students will engage with AI marketing tools, case studies, and simulations to develop practical skills applicable to real-world business challenges.
Course content

This course will cover the principles, tools, and strategic applications of Artificial Intelligence (AI) in modern marketing practices.

  1. Overview of Artificial Intelligence and Machine Learning in marketing

  2. AI’s role in digital transformation and marketing innovation

  3. Introduction to key AI marketing tools and platforms

  4. AI applications in market research and audience segmentation

  5. Predictive analytics and consumer behavior modeling using AI

  6. Generative AI for content development across digital channels

  7. AI-enhanced SEO and digital advertising techniques

  8. Personalization and recommendation systems powered by AI

  9. Consumer behaviour and psychological impacts of AI marketing

  10. AI strategies in social media marketing and trend analysis

  11. Ethical considerations, data privacy, and bias in AI marketing

  12. Current and emerging trends in AI for marketing strategy development

  13. Development and refinement of AI-driven marketing strategies

Learning activities

This course integrates theoretical learning with applied experience using the following methods:

  • Case Studies & Industry Engagement: Discussions and analyses of real-world AI marketing challenges.
  • Experiential Learning: AI simulations and marketing tool applications.
  • Project-Based Learning: Development of AI-driven marketing strategies for real or simulated businesses.
  • Work-Integrated Learning (WIL): Engagement with industry professionals through guest lectures, workshops, and networking events.
Means of assessment

Assessment will be based on course objectives and will be carried out in accordance with the 51Ç鱨վ Evaluation Policy. An evaluation schedule is presented at the beginning of the course. Instructors may use a student’s record of attendance and/or level of active participation in the course as part of the student’s graded performance. Where this occurs, expectations and grade calculations regarding class attendance and participation will be clearly defined in the Instructor Course Outline.

Assessment Component

Weight

Participation

5-10%

AI Simulations and Applied Exercises

20-30%

Assignments and Cases

15-20%

Term Project and Presentation

25-30%

Final Exam or Capstone Report

15-25%

STUDENTS MUST COMPLETE ALL COMPONENTS OF THE COURSE AND ACHIEVE A MINIMUM AVERAGE GRADE OF AT LEAST 50 PERCENT ON THEIR TOTAL NON-GROUP EVALUATIONS TO OBTAIN CREDIT FOR THE COURSE. 

Note: No single assignment to be worth more than 40%.

Students may conduct research as part of their coursework in this class. Instructors for the course are responsible for ensuring that student research projects comply with College policies on ethical conduct for research involving humans, which can require obtaining Informed Consent from participants and getting the approval of the 51Ç鱨վ Research Ethics Board prior to conducting the research.

 

 

 

 

 

Learning outcomes

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

  1. Explain AI’s role in marketing, including applications in machine learning, generative AI, and predictive analytics.
  2. Utilize AI tools for research, content creation, and customer engagement.
  3. Optimize digital marketing campaigns using AI-driven SEO, PPC, and automation.
  4. Analyze AI-generated marketing strategies and evaluate their effectiveness compared to human-created content.
  5. Assess ethical, legal, and strategic considerations in AI marketing applications.
  6. Develop and present an AI-powered marketing strategy for a business or simulated client.
Textbook materials

Required learning materials may include:

  • DMI Advanced AI for Digital Marketing (Core content replacing traditional textbook)
  • AI marketing tools: Free versions such as ChatGPT, Midjourney, Jasper AI, Google Gemini, SEMrush, Canva AI, and others.
  • Podcast case studies for real-world applications. Example - Marketing Corner Talks Podcast
  • Novela Generative AI Skills Simulation (if applicable for hands-on AI skill-building).

Latest edition or equivalent as approved by the Department.

Requisites

Prerequisites

MARK 3235

Corequisites

None

Equivalencies

None

Course Guidelines

Course Guidelines for previous years are viewable by selecting the version desired. If you took this course and do not see a listing for the starting semester / year of the course, consider the previous version as the applicable version.

(Current)

Course Transfers to Other Institutions

Below are current transfer agreements from 51Ç鱨վ to other institutions for the current course guidelines only. For a full list of transfer details and archived courses, please see the .

Institution Transfer details for MARK 3890
There are no applicable transfer credits for this course.

Course Offerings

There are no course offerings this semester.