Course Description
This course introduces students to Generative Artificial Intelligence and Large Language Models with a focus on practical applications for business. Students will learn the fundamentals and background of generative AI, possible applications, prompt engineering, and ethical considerations. They will also explore real-world applications in various business contexts. Prerequisite: ISM 110.
Syllabus
Student Learning Outcomes, Goals, Objectives:
Students successfully completing this course will be able to:
- Analyze foundational concepts of Large Language Models and Generative AI technologies, including their capabilities and limitations.
- Apply Generative AI tools to identify and solve common business problems across various functional areas.
- Create customized AI applications to address specific business needs and enhance decision-making.
- Evaluate ethical implications and develop frameworks for responsible application of Generative AI in business contexts.
Course Grading Information:
| Activity/Performance Measure | Percentage/Points |
|---|---|
| Quizzes | 10% |
| Discussion boards | 20% |
| Assignments | 30% |
| Project | 40% |
Grading Scale
| Percentage | Letter Grade |
|---|---|
| 93% and above | A |
| 90-92.99% | A- |
| 87-89.99% | B+ |
| 83-86.99% | B |
| 80-82.99% | B- |
| 77-79.99% | C+ |
| 73-76.99% | C |
| 70-72.99% | C- |
| As needed for lack of mastery | D+ |
| As needed for lack of mastery | D |
| As needed for lack of mastery | D- |
| As needed for lack of mastery | F |
Attendance/Participation:
This is an online course, with no required attendance or participation beyond assigned coursework.
Course Materials Purchased by the Students:
Course Packet: available for purchase at the following link https://hbsp.harvard.edu/import/1439396
Scholarly Perspectives
This course engages diverse scholarly perspectives to develop critical thinking, analysis, and debate and inclusion of a reading does not imply endorsement.