Detailed Course Information |
Fall 2024
Nov 12, 2024 |
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 | Click the Schedule Type to find available offerings of the course on the Schedule of Classes. |
| LOG 3252P - Mach Learning Apps-SC Plan |
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As the third course in the Supply Chain Analytics Professional program, you’ll be introduced to the field of machine learning, an area where algorithms learn patterns from data to support proactive decision making, as it applies to supply chain management. You’ll learn to forecast future demand and use this information to evaluate inventory policies, while also learning the importance of and how to perform customer segmentation. The course will cover regression (trees), advanced time series forecasting, various clustering techniques (such as k-means), decision trees, random forests, logistic regression. Using Power BI and Python, you’ll apply the techniques to sensor data of the fictional Cardboard Company’s paper production to build an anomaly detection model that supports proactive production maintenance planning.
While you are not required to complete the Transforming Supply Chain Management and Performance Analysis, Creating Business Value with Statistical Analysis, and Machine Learning Applications for Supply Chain Planning courses prior to this capstone, we suggest you being familiar with their learning outcomes.
Recommended Prerequisites:
General supply chain management knowledge
Elementary knowledge of statistics and data analysis along with basic coding skills
LOG 3250P - Transforming Supply Chain Management and Performance Analysis
LOG 3251P - Creating Business Value with Statistical Analysis
Required Prerequisite(s):
Python/programming experience
Power BI experience
1.400 Continuing Education Units 14.000 Lecture hours Syllabus Available Grade Basis: Z Logistics Institute Division Professional Education Department Course Attributes: Supply Chain Mgt, Sply Chn Analytics Prof |
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