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Introduction to Predictive Analytics

Today's leading businesses, governments, and other organizations collect large amounts of data about their operations and their customers. Classic examples are data about Amazon customers, call center data, or Twitter data. All that information is collected and then analyzed in order to predict future needs of individual customers, make sensible purchase suggestions to them, or try to market products and services directly to those customers. Another example is analysis of Google data that can be used for many purposes, for instance, to construct a model to predict outbreaks of infectious diseases based on sudden spikes in the frequency of certain words being googled.

Building such predictive models is part of Predictive Analytics, which is also associated with large amounts of unstructured data and a very broad range of practical applications. Companies move from traditional forms of predictive reporting to Predictive Analytics, so they can better react to changing environment. The companies want to be proactive rather than reactive.

In this two-day seminar you will learn basic skills in Predictive Analytics. You are going to harness the hidden power of Excel, and then use more sophisticated tools such as MINITAB® and R. Basic familiarity with Excel or other spreadsheet software is expected. 1.4 CEUs.

Topics include:

  • How to use Excel to retrieve data from Web on a predetermined schedule
  • How to make business decisions based on data
  • How to optimize operations in a call center
  • How to analyze text data such as a large number of product reviews
  • How to exploit association rules between individual customer preferences and product prevalence on the market
  • How to evaluate various marketing strategies

You will benefit by:
Collecting your own data from Websites Learning about software tools for Predictive Analytics. Learning about your customer base Using Predictive Analytics as an improvement on traditional reporting

Who should attend:
Managers, supervisors and other professionals who want to understanding and use Predictive Analytics. No prior experience with Minitab® or R is required. Basic familiarity with Excel or other spreadsheet software is expected.

Dates
Thursday, March 26 - Friday, March 27 8:30 am - 4:30 pm

Cost
$600.00 per person. Cost includes continental breakfast and lunch each day

Location
The RIT campus at the Center for Quality & Applied Statistics located in the Hugh L. Carey Building (building 14)

To register for this training please follow these directions:

  1. Please fill out the Registration Form

    REGISTRATION FORM

  2. If the form is not fillable when you open it, click on Open With Different Viewer on the top right of the form and click on Open With Adobe Reader
  3. If you do not have Adobe Reader, you can download it for free: https://get.adobe.com/reader/
  4. Once the form is filled out, please press submit on the bottom of the form and it will be emailed to us. You can click on Print on the bottom of the form and print a copy for your records.
    Note: Submitting the form does not work with Google Chrome. Please save the form and email it to cqasregistrations@rit.edu if you are using Google Chrome

Payment Information

1. Once we receive your registration form, we will email you a link to pay by credit card (or click on the link below).
2. We can also invoice your company, if that is your preference. (please check the invoice box on the registration form)

PAY NOW

Seminar registration will be confirmed upon receipt of a sufficient number of registrations.

Please Note: Registration must be received at least one week prior to the beginning of the training program.

Registration is also available by contacting:

Susan Chapman

 PHONE: (585) 475-6990
 FAX: (585) 475-5959
 E-MAIL: sjcpph@rit.edu

 

For more information, Contact:

Greg Evershed
Director of Business Development
gmecqa@rit.edu
585-475-5442
HLC/2526




 

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