Artificial Intelligence in planning and decisionmaking
B.Sc course, University of Debrecen, Department of Data Science and Visualization, 2024
The subject aims for students to learn the principles of artificial intelligence (AI) and their application in business planning and decision-making. During the classes, students gain insight into various AI technologies, such as machine learning, predictive modeling, and optimization algorithms. Special emphasis is placed on real industry examples and case studies, with the help of which students understand how these tools can be applied to solve various business challenges.
The course also covers the ethical issues of AI, such as transparency, avoiding bias, and regulatory and legal frameworks for decision-making. At the end of the course, students can try out the learned techniques in practice in a project and develop an AI-based solution to a real business problem.
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Email address of the Teacher
Requirements
- Attendance sheet: Fewer absences than allowed. Active participation in classes.
- Creating a working application and presenting it in the form of a video using the solutions and models learned in class.
- It must be uploaded to Github and shared.
- Maximum length of video is 5-10 minutes.
- In the video, each creator must present their own contribution.
- Organizing into teams (2-4 people) or working individually.
- If the creator(s) uses a service based on a generative language model to complete the task, then must attach the prompt log to the completed project as additional material.
- It is not sure that the team members receive a uniform grades, but get the grades in proportion to the task they have completed in the project.
- Submission deadline: 2024.12.02.
- Submission form
- Mandatory fields: Neptun code, Video link, Source link.
- If there are more than one of you, the Neptun code can be entered as a list separated by commas.
- The Source link contains the source code.
- The Video link contains the video code.
- If two are the same, the same must be entered in both places.
- If there are no exceptional obstacles, please allow (chose ‘yes’ on the form) your submitted work to be shared among the students of the following semesters within the framework of the subject.
Labor
- I. Introduction to AI and Decision Making (2024.09.16)
- II. Basics of decision-making and planning (2024.09.16)
- III. Data types (2024.09.23)
- IV. Visualizations (2024.09.30)
- V. Models 1. - Linear regression (2024.10.07)
- VI. Models 2. - Neural networks (2024.10.14)
- VII. Models 4. - Clustering (2024.10.28)
- VIII. Review creating with generative LLM (2024.11.04)
- IX. Prompt Engineering - Prompting (2024.11.11)
- IX. Prompt Engineering - Review-Analyst (2024.11.11)
- X. Prompt Engineering - Marketing-Generator (2024.11.18)
- X. Prompt Engineering - Random-Personas (2024.11.18)
- XI. Prompt Engineering - Chatbot
- XI. Prompt Engineering - Car Dealership AI Assistant
- XII. Final project and future prospects
- XIII. Guest speaker - Morgan Stanley (2024.12.09) Webex, Plan B (Teams)