IBM SPSS Certifications.

IBM SPSS training and certification programs enable you to maximize the value your IBM SPSS software provides you and your organization.
You can validate your expertise and advance your career by becoming certified in products that support analytics. Choose certification in IBM® SPSS® Statistics, for statistical analysis, or IBM® SPSS® Modeler, for data mining -- or become certified in both. Because these advanced software products are used and recognized globally, you can be sure that your certification will carry significance wherever your career takes you.

 

IBM Certified Specialist - SPSS Statistics Level
This certification is for individuals with a working knowledge of IBM SPSS Statistics version 15 or higher, including: analysts, statisticians, and individuals in academia, business, or research who use the IBM SPSS product. The IBM Certified Specialist - SPSS Statistics Level may utilize the IBM SPSS Statistics product for predictive analysis, market research and statistical research.

Course title: Introduction to IBM SPSS Statistics
Course duration: 2 days
Overview: Get up to speed in IBM SPSS Statistics V19 (formerly SPSS Statistics) quickly and easily in this course.
The course guides you through the fundamentals of using IBM SPSS Statistics for typical data analysis process. Learn the basics of reading data, data definition, data modification, and data analysis and presentation of your results. See how easy it is to get your data into IBM SPSS Statistics so that you can focus on analyzing the information. In addition to the fundamentals, learn shortcuts that will help you save time. This course uses the IBM SPSS Statistics Base features.

Course title: Introduction to Statistical Analysis Using IBM SPSS Statistics

Course duration: 2 days
Overview: The focus of this course is an introduction to the statistical component of IBM SPSS Statistics Base V19.
This is an application-oriented course and the approach is practical. You'll take a look at several statistical techniques and discuss situations in which you would use each technique, the assumptions made by each method, how to set up the analysis using IBM SPSS Statistics as well as how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing underlying relationships. You will gain an understanding of when and why to use these various techniques as well as how to apply them with confidence, and interpret their output, and graphically display the results using IBM SPSS Statistics. This course uses the IBM SPSS Statistics Base features.

Course title: Data Management and Manipulation with IBM SPSS Statistics
Course duration: 2 days
Overview: The focus of this course is on the use of a wide range of transformation techniques to modify data values, ways to automate your work, manipulate your data files and results, and export your results to other applications' file formats. You will gain an understanding of the various options for controlling the IBM SPSS Statistics V19 (formerly SPSS Statistics) operating environment and how to use basic syntax to perform data transformations efficiently and automate your work. This course uses the IBM SPSS Statistics Base features.

 

IBM Certified Specialist - SPSS Modeler Professional
This certification is for individuals with a working knowledge of IBM SPSS Modeler version 14 or higher working in government, academia, or business who use the IBM SPSS Modeler product to perform data mining activities including data preparation, data understanding, and modeling.

The IBM Certified Specialist - SPSS Modeler Professional may utilize the IBM SPSS Modeler product for applications such as fraud detection, customer management and churn, risk management, and so forth.

Course title: Introduction to IBM SPSS Modeler and Data Mining
Course duration: 3 days
Overview: This course provides an overview of data mining and the fundamentals of using IBM SPSS Modeler. Using the CRISP-DM methodology, the principles and practice of data mining are illustrated. The course structure follows the stages of a typical data mining project, from reading data, to data exploration, data transformation, modeling, and effective interpretation of results. The course provides training in the basics of how to read, explore, and manipulate data with IBM SPSS Modeler, and then create and use successful models.

Course title: Predictive Modeling with IBM SPSS Modeler
Course duration: 3 days
Overview: This course demonstrates how to develop models to predict categorical and continuous outcomes, using such techniques as neural networks, decision trees, logistic regression, support vector machines, and Bayesian network models. Use of the binary classifier and numeric predictor nodes to automate model selection is included. Feature selection and detection of outliers are discussed. Expert options for each modeling node are reviewed in detail and advice is provided on when and how to use each model. You will also learn how to combine two or more models to improve prediction. Independent Study Only: Syllabus is provided for each week's study and materials are completed privately by each participant. 1 time per week students will meet on-line to review course exercises with a Live Instructor.

Course title: Clustering and Association Models with IBM SPSS Modeler
Course duration: 1 day
Overview: This course demonstrates how to segment or cluster data with all the clustering techniques available in IBM SPSS Modeler. The course also provides examples of creating association models to find rules describing the relationships among a set of items, and of creating sequence models to find rules describing the relationships over time among a set of items.

Course title: Advanced Data Preparation with IBM SPSS Modeler
Course duration: 1 day
Overview: In this course, you will examine additional topics to aid in the preparation of data for a successful data mining project. You will learn how to partition records from files, handle missing data, modify fields and create new fields, and work with dates, strings and sequence data.

  
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