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SCM.256

Data Science and Machine Learning for Supply Chain Management

5-0-7 units · Graduate

Introduces data science and machine learning topics in both theory and application. Data science topics include database and API connections, data preparation and manipulation, and data structures. Machine learning topics include model fitting, tuning and prediction, end-to-end problem solving, feature engineering and feature selection, overfitting, generalization, classification, regression, neural networks, dimensionality reduction and clustering. Covers software packages for statistical analysis, data visualization and machine learning. Introduces best practices related to source control, system architecture, cloud computing frameworks and modules, security, emerging financial technologies and software process. Applies teaching examples to logistics, transportation, and supply chain problems. Enrollment limited.

Prerequisites & course information

Prereq: SCM.254 or permission of instructor G (Spring) 5-0-7 units

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