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Fast Track your Knowledge of SPSS with
Pre-Conference and Post-Conference Training Courses


Hands-on Courses

Get hands-on experience working with applications. Choose from a variety of half day or full day courses taught by SPSS Inc. instructors. You must be registered for Directions to sign up for these courses. Seating is limited and training sessions sell out.


New! Lecture Series: Concepts in Practice

Join acclaimed speaker Dr. Alok Choudhary for a special, high-level course on "High Performance Analytics and Data Mining for Strategic Competitive Advantage." Dr. Choudhary will provide practical examples of usage in the marketplace, and describe the results, benefits, and ROI that can be achieved with analytics and data mining. The cost of this premium course is $799, and it will take place over two days (Wednesday afternoon and Thursday morning). More information.



PRE-CONFERENCE COURSES

Sunday, November 9, 2008

Clementine v.12: New Predictive Models ($349)

Building Dashboards and Customized Reports for Web Delivery with Predictive Enterprise Services ($349)

Correspondence Analysis and Multidimensional Scaling using SPSS Categories ($349)

Best Practices for Dimensions Scripting ($349)

Introduction to SPSS Neural Networks ($349)

Customer Segmentation & Classification Trees
using SPSS Statistics 17 ($349)



POST-CONFERENCE COURSES

Wednesday and Thursday, November 12-13, 2008

Introduction to SPSS Text Analysis for Surveys ($599)

Business Forecasting and Trend Analysis with SPSS Forecasting ($599)

Introduction to Statistical Analysis with SPSS Statistics Base ($599)

Introduction to SPSS Categories, Customer Segmentation & Classification Trees (Survey/Market Research) ($599)

High-Performance Analytics and Data Mining
for Strategic Competitive Advantage ($799)

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High-Performance Analytics and Data Mining
for Strategic Competitive Advantage
Prof. Alok Choudhary

Synopsis
In the rapidly changing business environment of global competition and maturing markets, competitive advantage is extremely important to analyze and mine data to extract pertinent knowledge, build efficient processes, develop strategic decision making procedures, to drive a company’s competitive advantage Solving the problem of creating and implementing intelligent analytical processes is a major focus of technology professionals and managers throughout the corporate world. This one day seminar presents competitive tactics using high-performance analytics and data mining that will enable attendees to determine strategies, roadmaps and challenges for his/her organization.

Sample strategic business applications that will be addressed using this high-performance analytical methodology include the following capabilities to:

  1. Find, grow and keep loyal and profitable customers requires managing the customer life-cycle based on sophisticated mining and analytics to acquire, grow and retain customers.
  2. Optimize supply chains and business processes, marketing and marketing resource management.
  3. Predict future customer needs in a personalized manner, detecting fraud, managing risks and predicting values of customers and partners.
  4. Develop new products using real-time experiments for designing products, customizing and marketing products and bundles.
  5. Research emerging areas of biotechnology industries such as designing personalized drugs and treatments, or determining genetic and chemical causes of certain diseases and potential treatments and therapies.

Objectives
By the end of this seminar, attendees will be able to:

Presenter
The seminar has been developed by Dr. Alok N. Choudhary. Professor Choudhary is a professor in the Marketing Department at Kellogg School of Management and in the Electrical and Computer Engineering Department at the McCormick School of Engineering and Applied Science at Northwestern University.

Audience
This seminar is designed for a broad audience including managers, IT personnel, engineers, and researchers, within the business fields of marketing, sales, finance, human resources, customer service, supply chain, accounting, and quality control.


Clementine v.12: New Predictive Models

This course is designed to familiarize Clementine users with the new predictive models available in Clementine v.12. This course will discuss the type of data needed for each model, the advanced user options for each model, and how to interpret the results of each model. This course includes hands-on training on

Prerequisite: Experience with Clementine or completion of the Introduction to Clementine course.

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Building Dashboards & Customized reports for
Web Delivery with Predictive Enterprise Services

This course will focus on how to build a dashboard in ShowCase 8 using PES and tag library. You will create a web page using reports and tag library to create your dashboard in PES. After a brief introduction to how tag libraries work, the course includes hands-on training on

If you are a ShowCase 8 PES user who wants to learn more about the use of tag libraries to design dashboards, this course will be of interest to you.

Prerequisite: Experience with Query, ReportWriter and PES

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Correspondence Analysis and Multidimensional
Scaling using SPSS Categories

This course will focus on how to perform Correspondence Analysis and Multi-Dimensional Scaling using SPSS Statistics. The course will focus on how to set up these analyses and to interpret the results. The course includes hands-on training on

If you are an SPSS user in any field who wants to learn more about Correspondence analysis and Multidimensional Scaling, this course will be of interest to you.

Prerequisite: Experience with SPSS or completion of the Introduction to SPSS (Basics) course. Basic statistical knowledge or at least one college level course in statistics is helpful.

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Best Practices for Dimensions Scripting

The workshop will walk you through the Dimensions Interview object models and:

Prerequisite: People who are proficient with Dimensions IOM scripting through mrStudio, but would like some tips and best practices on how to streamline their work and make things more efficient.

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Introduction to SPSS Neural Networks

This course will focus on how to build a neural network with SPSS Statistics Neural Networks. The resulting models will be examined and the output explained. In addition, we will introduce and discuss the types of algorithms within the SPSS Neural Net module. After a brief introduction to how Neural Networks work, the course includes hands-on training on the following features

If you are an SPSS user in any field who wants to learn more about the use of Neural Networks for predictive modeling, this course will be of interest to you.

Prerequisite: Experience with SPSS or completion of the Introduction to SPSS (Basics) course. Basic statistical knowledge or at least one college level course in statistics is helpful.

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Customer Segmentation and Classification Trees
using SPSS Statistics 17

This course will focus on the statistical techniques most often used to support market segmentation, and decision tree modeling using SPSS. The course emphasizes the practical issues of setting up and running the analysis in SPSS, and interpreting the results. The course includes hands-on training on:

If you are an SPSS user in any field who wants to learn more about segmentation and classification methods, this course will be of interest to you.

Prerequisite: Experience with SPSS for Windows or completion of the Introduction to SPSS (Basics) course. Basic statistical knowledge or at least one college level course in statistics is helpful.

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Introduction to SPSS Text Analysis for Surveys

This course will overview how to analyze text or open-ended survey questions using SPSS Text Analysis for Surveys. You will see the steps involved in working with text data, from reading the text data to exporting the final categories for additional analysis. Topics include how to automatically and manually create and modify categories, and how to edit synonym, type, and exclude dictionaries:

If you conduct survey research and want to learn about how to use SPSS Text Analysis for Surveys software to help you understand and categorize text open-ended question responses, this course will be of interest to you.

Prerequisite: No previous experience with SPSS Text Analysis for Surveys software is expected. Experience in hand-coding verbatim survey responses is helpful.

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Business Forecasting and Trend Analysis with SPSS Forecasting

This course will focus on how to perform Time Series Analysis in SPSS Forecasting with the expert modeler. The course emphasizes the practical issues of setting up and running a time series analyses in SPSS Forecasting, and interpreting the results. The course includes hands-on training on

If you are an SPSS user in any field who wants to learn more about Time Series analysis methods, this course will be of interest to you.

Prerequisite: Experience with SPSS or completion of the Introduction to SPSS (Basics) course. Basic statistical knowledge or at least one college level course in statistics is helpful.

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Introduction to Statistical Analysis with SPSS Statistics Base

This course is an introduction to statistical analysis. We will cover several statistical techniques and discuss situations in which you would use each technique. We will also discuss the assumptions made by each method, how to set up the analysis using SPSS, as well as how to interpret the results. This course includes hands-on training on:

Prerequisite: Experience with SPSS or completion of the Introduction to SPSS (Basics) course.

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Introduction to SPSS Categories, Customer Segmentation
& Classification Trees (Survey/Market Research)

Learn how to perform Correspondence Analysis and Multi-Dimensional Scaling using SPSS Statistics. The course will focus on how to set up these analyses and to interpret the results. Also learn the statistical techniques most often used to support market segmentation, and decision tree modeling using SPSS. The course emphasizes the practical issues of setting up and running the analysis in SPSS, and interpreting the results. The course includes hands-on training on:

Prerequisite: Experience with SPSS or completion of the Introduction to SPSS (Basics) course. Basic statistical knowledge or at least one college level course in statistics is helpful. Experience with SPSS for Windows or completion of the Introduction to SPSS (Basics) course. Basic statistical knowledge or at least one college level course in statistics is helpful.