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Data Mining 201 using Analytic Solver
Enrollment in this course is by invitation only

The objective of this course is to provide students with a more in-depth data mining learning experiencing using Analytic Solver Data Mining. The information provided in this course builds on the existing foundation gained from the Data Mining 101 course for students planning to use data mining to address business problems using the Analytic Solver software.

Enrollment in this course is by invitation only

About This Course

This is an advanced data mining course using Analytic Solver Data Mining. This course delves deeper into data mining and forecasting topics. Take this course to learn more about Nueral Networks and other classification and regression methods and also to learn how to use Analytic Solver Data Mining for forecasting future behavior using smoothing methods and other predictive analytics.

Requirements

Students must have already taken and passed the Data Mining using Analytic Solver course.

Course Staff

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Nicole Steidel

Nicole Steidel has a Masters degree in Quantitative Analysis and an MBA from the University of Cincinnati and has been with Frontline Systems for over 15 years. She served for over 4 years on the technical support team and then has moved on to Product Documentation and Development. During her tenure at Frontline, she has had the opportunity to assist many customers by answering questions concerning Solver products or assisting them with their own model creation.

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Sima Maleki

Dr. Sima Maleki works as consulting lead and analytics modeling specialist for Frontline Systems. As part of her work, Sima helps companies around the world effectively use analytics to leverage business opportunities and make better decisions. She also regularly teaches live educational webinars on data mining, optimization, and simulation and risk analysis (www.solver.com/webinars).

Enrollment in this course is by invitation only