Formation Introduction à IBM SPSS Modeler et à la Science des Données (v18.1.1)

This course provides the fundamentals of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides training in the basics of how to import, explore, and prepare data with IBM SPSS Modeler v18.1.1, and introduces the student to modeling.

Public :

Ce cours SPSS Modeler et Data Science s'adresse aux business analysts, data scientists et plus globalement par toute personne intéressée par IBM SPSS Modeler.

Prérequis :

Il est recommandé d'avoir une connaissance des données de son business pour suivre cette formation IBM SPSS Modeler.

Introduction to data science

List two applications of data science
Explain the stages in the CRISP-DM methodology
Describe the skills needed for data science

Introduction to IBM SPSS Modeler

Describe IBM SPSS Modeler's user-interface
Work with nodes and streams
Generate nodes from output
Use SuperNodes
Execute streams
Open and save streams
Use Help

Introduction to data science using IBM SPSS Modeler

Explain the basic framework of a data-science project
Build a model
Deploy a model

Collecting initial data

Explain the concepts "data structure", "of analysis", "field storage" and "field measurement level"
Import Microsoft Excel files
Import IBM SPSS Statistics files
Import text files
Import from databases
Export data to various formats

Understanding the data

Audit the data
Check for invalid values
Take action for invalid values
Define blanks

Setting the of analysis

Remove duplicate records
Aggregate records
Expand a categorical field into a series of flag fields
Transpose data

Integrating data

Append records from multiple datasets
Merge fields from multiple datasets
Sample records

Deriving and reclassifying fields

Use the Control Language for Expression Manipulation (CLEM)
Derive new fields
Reclassify field values

Identifying relationships

Examine the relationship between two categorical fields
Examine the relationship between a categorical field and a continuous field
Examine the relationship between two continuous fields

Introduction to modeling

List three types of models
Use a supervised model
Use a segmentation model