Training Opportunities: Post-Conference Training
EMEA Directions Post Conference Training
Wednesday
16th May 2007 - Prague
09:00 – 16:00
Fee: € 450
Click here for a full-listing of pre-conference training courses.
Hands-on Application of Clementine for Clustering and Predictive Modeling (1 Day Session)
Fee: € 450
Full-day hands-on training led by an industry expert focuses on both clustering techniques and predictive modeling skills using a mock database.
- Specific hands-on topics include:
- Extracting data from a transactional data warehouse
- Preparing data into analytical file format
- Conducting data audit, visualization
- Using TwoStep, K-means clustering nodes
- Using Neural Net, C&RT, Chaid and Kohonen predictive modeling nodes Lecture portions include:
- Concepts in segmentation
- Potential use of data mining
- Tiered Knowledge Management Model (TKMM)
- CRISP-DM
Note: This session is intended for analysts, data warehousing and BI professionals who have the interest in pursuing business analytics and have no or limited experience of Clementine. The course requires a basic understanding of basic statistical concepts and a general understanding of data warehousing/data mart technologies and data mining.
Survey Analysis Using SPSS (1 Day Session)
Fee: € 450
This session provides a hands-on introduction detailing methods of conducting
analysis on survey data. Appropriate methods of analysis are discussed for
both categorical and continuous data. Steps to produce and interpret
five procedures, with appropriate statistical tests are presented.
Specific topics include:
- Cross-tabulation, with Chi-square tests (including its limitations)
- Multiple Response analysis (check all that apply “questions”)
- Comparing mean differences, including
- T-tests
- Analysis of Variance (ANOVA)
- Introduction to Regression
Introduction to Time Series Analysis with SPSS Expert Modeler (1 Day Session)
Fee: € 450
The goal of this course is to introduce you to how to use the Expert Modeler
to perform forecasting with SPSS Trends.
The course will begin with a discussion of the basic principles of Times Series
Analysis, and will include examples of Exponential Smoothing and ARIMA models,
ways to assess each model’s performance, and how to apply saved models to existing
or new data.
- The Basics of Time Series
- Automatic Forecasting with Time Series Modeler
- Measuring Model Performance
- Exponential Smoothing Models
- ARIMA Models
- Applying Time Series Models