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Predictive Analytics

Three business people discuss graphs on screen in meeting room
COM SCI X 450.7

This hands-on course helps you use predictive analytics for improving business performance using techniques such as data mining, statistics, modeling, machine learning, and artificial intelligence.

Duration
As few as 11 weeks
Units
4.0
Current Formats
Online
Cost
Starting at $1,100.00

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What you can learn.

Define/explain the role and capabilities of a predictive analytics engineer
Develop expertise in both optimization techniques and predictive modeling
Learn how to implement industry-standard analytics applications including churn prediction, A/B testing, and customer lifetime value modeling

About This Course

Dive into concepts and techniques of predictive analytics and model engineering. Students will develop proficiency in Python programming language, with special emphasis on forecasting methodologies, optimization techniques, and product analysis frameworks. The course covers real-world applications including customer churn prediction, A/B testing analysis, demand forecasting, and pricing optimization(i.e. via deep learning, objective functions, classification trees, NLP or other models). Students will learn data preprocessing, model development, evaluation metrics, and the application of machine learning algorithms to solve high-impact business problems.
Prerequisites
Recommended: COM SCI X 450.1 Introduction to Data Science.

Summer 2026 Schedule

Date
Details
Format
 
-
This section has no set meeting times.
Instructor:
REG#
408965
Fee:
$1,100.00
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Notes
Enrollment limited; early enrollment advised. Enrollment deadline: June 28th, 2026.
Deadline
No refunds after June 15, 2026