AI in Business and Society 2600-IBP-AIBandS
1. An Introduction to AI and its relationship with you
2. AI Development process
3. Data Preprocessing
4. Machine Learning Models
5. Deep Learning
6. Natural Language Models (NLMs)
7. Large Language Models (LLMs)
8. Impact of AI on business & societies
9. Trustworthy AI
Course coordinators
Term 2025L: | Term 2025Z: | Term 2026Z: |
Type of course
Learning outcomes
Upon completion of this seminar, the student should be able to:
• Analyse the various types of AI and evaluate their potential applications in different business and societal contexts.
• At a non-technical level, apply data pre-processing techniques to prepare data for use in machine learning models and evaluate the impact of these techniques on model performance.
• At a non-technical level, create a deep learning model to solve a complex business problem, using appropriate algorithms and data structures.
• Research the impact of AI on business operations and societal dynamics, including its potential benefits and challenges.
• Debate, research and communicate ethical and responsible AI practices and evaluate the impact of these practices on society and the economy
Assessment criteria
1. Class Participation - Attendance & in-class discussion for problem solving exercise (50%)
2. Group Project - including Applied Practical work (50%)