Syllabus

Title
2534 Generative AI Applications in Marketing
Instructors
Sumon Chaudhuri, PhD
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
09/13/24 to 09/19/24
Registration via LPIS
Notes to the course
Dates
Day Date Time Room
Friday 10/25/24 09:00 AM - 12:00 PM EA.5.040
Friday 10/25/24 01:00 PM - 03:00 PM EA.5.040
Friday 11/08/24 09:00 AM - 12:00 PM TC.3.03
Friday 11/15/24 09:00 AM - 12:00 PM D5.1.001
Friday 11/22/24 09:00 AM - 12:00 PM D2.0.374
Friday 12/06/24 09:00 AM - 12:00 PM TC.4.03
Friday 12/13/24 09:00 AM - 12:00 PM TC.5.12
Friday 12/20/24 09:00 AM - 12:00 PM TC.5.12
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

Students will learn:

  1. What is Gen-AI and what are the things it can do.
  2. What are some popular 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

Students are expected to attend all 8 units of the course and are expected to participate in class.

In exceptional cases (e.g., sick leave), students might inform the lecturer and are allowed to miss at most one unit. That means that the extent of compulsory attendance is 7 units.

The course takes place on campus and in presence mode.

Teaching/learning method(s)
  • Instructions by trainer
  • Practical workshops on Gen-AI tools (like ChatGPT and Dall-e)
  • Assignments
  • Illustration through business use-cases
Assessment

30% : Report generation assignment

35% : Group assignment

35% : Data analysis assignment

The grading scheme is as follows:

  • < 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

Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.

Last edited: 2024-08-29



Back