Introduction to IBM SPSS Modeler and Data Science (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.

SKU: 1. Category: SPSS, SPSS

Description

At Sixe Engineering we have been providing official IBM training around the world for over 12 years. Get the best training from our specialists in Europe. We have important discounts and offers for two or more students.

Course details

IBM course code: 0A008G	Category: IBM SPSS Modeler / IBM SPSS Modeler
Delivery: Online & on-site**	Course length in days: 2

Target audience

• Business analysts

• Data scientists

• Clients who are new to IBM SPSS Modeler or want to find out more about using it

Desired Prerequisites:

• It is recommended that you have an understanding of your business data

Instructors

The great majority of the IBM courses we offer are taught directly by our engineers. This is the only way we can guarantee the highest quality. We complement all the training with our own materials and laboratories, based on our experience during the deployments, migrations and courses that we have carried out during all these years.

Added value

Our courses are deeply role oriented. To give an example, the needs for technology mastery are different for developer teams and for the people in charge of deploying and managing the underlying infrastructure. The level of previous experience is also important and we take it very seriously. That is why beyond (boring) commands and tasks, we focus on solving the problems that arise in the day to day of each team. Providing them with the knowledge, competencies and skills required for each project. In addition, our documentation is based on the latest version of each product.

Agenda and course syllabus

1. Introduction to data science

• List two applicatinons of data science

• Explain the stages in the CRISP-DM methodology

• Describe the skills needed for data science

2. 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

3. Introduction to data science using IBM SPSS Modeler

• Explain the basic framework of a data-science project

• Build a model

• Deploy a model

4. 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

5. Understanding the data

• Audit the data

• Check for invalid values

• Take action for invalid values

• Define blanks

6. Setting the of analysis

• Remove duplicate records

• Aggregate records

• Expand a categorical field into a series of flag fields

• Transpose data

7. Integrating data

• Append records from multiple datasets

• Merge fields from multiple datasets

• Sample records

8. Deriving and reclassifying fields

• Use the Control Language for Expression Manipulation (CLEM)

• Derive new fields

• Reclassify field values

9. 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

10. Introduction to modeling

• List three types of models

• Use a supervised model

• Use a segmentation model

Do you need to adapt this syllabus to your needs? Are you interested in other courses? Ask us without obligation.

Locations for on-site delivery