Syllabus
Registration via LPIS
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 |
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.
Students will learn:
- What is Gen-AI and what are the things it can do.
- What are some popular Gen-AI tools.
- How they can use Gen-AI to generate texts, images and programs for practical business applications.
- Scenarios where they can use Gen-AI to boost productivity.
- What are things they should be careful about while using Gen-AI.
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.
- Instructions by trainer
- Practical workshops on Gen-AI tools (like ChatGPT and Dall-e)
- Assignments
- Illustration through business use-cases
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)
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