ISOM-835 Predictive Analytics and Machine Learning

This course merges predictive analytics with machine learning, focusing on Python for practical, real-world applications. Students will develop skills in sophisticated analysis, data-driven prediction, and strategic decision-making. The topics include:

Python Application: Leveraging Python for data manipulation, analysis, and model building.
Business Analytics Lifecycle: Covering all phases from conception to deployment, with a Python-centric approach.
Data Management and Preprocessing: Using Python for efficient data handling.
Advanced Modeling Techniques: Focusing on regression, ensemble learning, and Python's machine learning libraries.
Model Evaluation and Optimization: Techniques for model assessment and improvement using Python.
Machine Learning Algorithms: Exploring a range of supervised and unsupervised learning methods in Python.

Designed for those aiming for advanced roles in data analytics and machine learning, this course equips students with highly sought-after skills in today's data-centric business world.

Credits

Prerequisite

Student has satisfied all of the following Academic Unit (Computed) in the selection list Accounting, Accounting and Business Law, Business Administration, Business Administration Executive, Business Analytics, Business Law and Ethics, Entrepreneurship, Finance, Health Administration, Information System, Information Systems and Operations Management, INTO Sawyer Business School, Management and Entrepreneurship, Management Studies, Marketing, Moakley Center for Public Management, Public Administration, Public Administration and Health Administration, Sawyer Business School, Strategy and International Business Or Programs of Study any in the selection list Business Economics Major BSBA