EXCPE 4787 - Machine Learning Foundations

Course Description

This is a must-have course for professionals who are seeking foundational, conceptual, and technical knowledge in machine learning. Learn how to analyze the credibility of artificial intelligence/machine learning and its applications in business. Gain an understanding of unsupervised, supervised, and reinforcement learning, the three widely accepted categorizations of machine learning.

Learner Outcomes

Students will be able to speak confidently about and develop informed opinions about ML and AI. Students will be introduced to the three main types of machine learning and how they are used in a business context. Students will have a working knowledge of how to define a business problem and turn it into a workable ML question. They will also be introduced to the properties of a healthy data pipeline for ML, and the ethical issues which need to be considered when doing an ML project. Knowledge Demystifying AI Understand how the three types of ML are used in business Understand the major issues of data use and collection How to go about turning a business problem into an ML question Ethical issues connected to ML Skills Have well-informed discussions on AI Identify the three types of ML and how they are used Identify the properties of a healthy data pipeline Identify a business problem, and turn it into an ML question Effectively address common ethical issues in ML Integration Look at what you know (or think you know) before and after the class. Has your understanding changed? Case Studies: How, specifically, is ML used in business? Put it all together in an initial ML project plan for the final assignment