Program Overview

Predictive Analytics Program

The Predictive Analytics program is a hands-on course that helps students use predictive analytics to improve business performance. The program covers techniques such as data mining, statistics, modeling, machine learning, and artificial intelligence.

Program Description

The program dives 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 program covers real-world applications including customer churn prediction, A/B testing analysis, demand forecasting, and pricing optimization.

Program Details

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

What You Can Learn

• Identify instances where predictive analytics could be employed to gain insights for making good decisions
• Use predictive analytics to solve business, marketing, and economic problems

Prerequisites

• Recommended: COM SCI X 450.1 Introduction to Data Science

Schedule

Spring 2026 Schedule

• Date: March 30 - June 8
• Format: Online
• Instructor: Ali El-Annan
• Fee: $1,100.00
• Notes: Enrollment limited; early enrollment advised. Enrollment deadline: April 5th, 2026.
• Deadline: Refunds only available from February 02, 2026 to April 12, 2026

Summer 2026 Schedule

• Date: June 22 - August 31
• Format: Online
• Instructor: Ali El-Annan
• Fee: $1,100.00
• Notes: Enrollment limited; early enrollment advised. Enrollment deadline: June 28th, 2026.
• Deadline: No refunds after June 15, 2026

Program Outcomes

The Predictive Analytics program is designed to help students develop skills in predictive analytics and model engineering, and apply these skills to solve real-world business problems. Upon completion of the program, students will be able to identify instances where predictive analytics can be employed, and use predictive analytics to solve business, marketing, and economic problems.