Syllabus

Title
6281 Generative AI Applications in Marketing
Instructors
Sumon Chaudhuri, PhD
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
02/17/25 to 02/24/25
Registration via LPIS
Notes to the course
Dates
Day Date Time Room
Thursday 03/13/25 08:00 AM - 11:00 AM TC.3.07
Thursday 03/20/25 08:00 AM - 11:00 AM TC.3.07
Thursday 03/27/25 08:00 AM - 11:00 AM TC.3.07
Thursday 04/03/25 08:00 AM - 11:00 AM D5.1.002
Thursday 04/10/25 08:00 AM - 11:00 AM TC.3.07
Friday 04/11/25 08:00 AM - 11:00 AM TC.3.07
Thursday 04/24/25 08:00 AM - 11:00 AM TC.3.07
Friday 04/25/25 08:00 AM - 10:00 AM TC.3.07
Contents

Generative AI (Gen-AI) is rapidly gaining popularity as a tool that can accelerate productivity. It can be used to generate large volumes of text and images catered to meet specific business requirements quickly and comprehensively. In dynamic business environments, mastery of Gen-AI tools can be a crucial differentiator that enables users to streamline their projects.

In this course, students will learn how to practically use Gen-AI in a variety of contexts. They will gain a broad understanding of Gen-AI tools (like ChatGPT and Dall-e), and learn ways in which these tools can be used most effectively. This includes tasks like writing reports, generating creative content, and writing programs.

They will also learn about the limitations of these tools, the general “dos and don’ts” of using Gen-AI tools, and the ethical implications of using such tools in the workplace.

Learning outcomes
  1. What is Gen-AI and what are the things it can do.
  2. How to get the best out of Gen-AI tools.
  3. How they can use Gen-AI to generate texts, images and programs for practical business applications.
  4. Scenarios where they can use Gen-AI to boost productivity.
  5. What are things they should be careful about while using Gen-AI.
Attendance requirements

80% of classes should be attended

Teaching/learning method(s)
  1. Instructions by trainer
  2. Practical workshops on Gen-AI tools (like ChatGPT and Dall-e)
  3. Assignments
  4. Illustration through business use-cases
Assessment
  • 30% : Report generation assignment
  • 35% : Group assignment
  • 35% : Data analysis assignment

< 60%                         fail (5)
60% to 69,99%           sufficient (4)
70% to 79,99%           satisfactory (3)
80% to 89,99%           good (2)
>= 90%                       excellent (1)

Readings

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Last edited: 2024-12-05



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