This course, an integral part of the Executive Master in AI for Business program, aims to provide participants with a comprehensive understanding of machine learning methodologies and their applicability in various business sectors. The course includes three intensive lectures covering fundamental machine learning principles, advanced learning paradigms, different data representations, and essential business analytics tools, supplemented with real-world case studies.

Instructor

Professor Stefano Zingaro
University of Bologna
Email: stefano.zingaro@unibo.it
Office Hours: By appointment

Teaching Methods

• Theoretical background and interactive lectures
• Case studies focusing on recent business scenarios
• Hands-on labs using tools like Python and GUI-based applications
• Teamwork and collaboration on specific assignments
• Guest speaker lectures from industry experts

Pre-Course Readings

• "Introduction to Machine Learning" - Dive into Deep Learning
• "Machine Learning in Business: An Overview" - Forbes
• "Critical Perspectives on Machine Learning" - Critical Field Guide to Machine Learning
• "Understanding AI and its Broad Impacts" - Anatomy of an AI System

Intended Learning Outcomes (ILOs)

• Comprehensive technical mastery of AI and ML techniques
• Hands-on experience with diverse AI and ML applications
• Integration of AI and ML into business processes
• Assessment of the business impact of AI
• Ethical considerations in AI implementation

Class Schedule and Assignments

Session 1: Introduction to Machine Learning in Business

• Date: December 12, 2023 – 18:30 – 21:30
• Location: Online - Microsoft Teams
• Content: Introduction to the course, overview of machine learning types and business applications, discussion of advanced learning paradigms and data representation, the role of machine learning in modern business decision-making.
• Case Study: Predictive Analytics for Customer Retention in a Retail Business.
• Assignment: Individual reflection on how machine learning can impact the participant’s current business role. Due: Second lecture.

Session 2: Machine Learning Tools and Techniques in Business

• Date: December 14, 2023 – 18:30 – 21:30
• Location: Online - Microsoft Teams
• Content: Business Analytics Tools, practical application of ML in business analytics, case study analysis and group discussion, Machine Learning Tools Workshop.
• Case Studie: Customer Profiling in a BMW Car Dealership; Customer Segmentation in Online Retail; Startup profiling from Investments (Crunchbase).
• Assignment: Analysis of the BMW dealership case study. Due: Start of Lecture 3.

Session 3: Machine Learning in Decision Making and Explainability

• Date: December 19, 2023 – 18:30 – 21:30
• Location: Online - Microsoft Teams
• Content: Decision trees and ensemble methods, introduction to explainability in machine learning, fairness, accountability, and transparency in ML.
• Supplementary Reading: "Why Should I Trust You?": Explaining the Predictions of Any Classifier.
• Guest Speaker: Mirko Savasta, Head of Quant Research @ Axyon AI.
• Case Study: Clustering Companies Based on Stock Price Movements.
• Assignment: Team proposal for an explainable AI project addressing a specific business problem. Due: End of the course.

Plagiarism Policy

Refer to the plagiarism policy details page for the University of Bologna.

Disclaimer

The information in this syllabus may be subject to moderate changes. Any modifications will be communicated to students.