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|IBM course code: 0A058G||Category: IBM SPSS Modeler / IBM SPSS Modeler|
|Delivery: Online & on-site**||Course length in days: 1|
This advanced course is intended for anyone who wants to become familiar with the full range of techniques available in IBM SPSS Modeler for data preparation.
• Experience using IBM SPSS Modeler including familiarity with the Modeler environment, creating streams, reading data files, exploring data, setting the unit of analysis, combining datasets, deriving and reclassifying fields, and basic knowledge of modeling.
• Prior completion of the Introduction to IBM SPSS Modeler and Data Science course is recommended.
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.
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: Using functions to cleanse and enrich data
• Use date functions
• Use conversion functions
• Use string functions
• Use statistical functions
• Use missing value functions
2: Using additional field transformations
• Replace values with the Filler node
• Recode continuous fields with the Binning node
• Change a field’s distribution with the Transform node
3: Working with sequence data
• Use sequence functions
• Count an event across records
• Expand a continuous field into a series of continuous fields with the Restructure node
• Use geospatial and time data with the Space-Time-Boxes node
4: Sampling, partitioning and balancing data
• Draw simple and complex samples with the Sample node
• Create a training set and testing set with the Partition node
• Reduce or boost the number of records with the Balance node
5: Improving efficiency
• Use database scalability by SQL pushback
• Process outliers and missing values with the Data Audit node
• Use the Set Globals node
• Use parameters
• Use looping and conditional execution
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
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- Estonia: Tallinn
- Finland: Helsinki
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- Italy: Rome
- Louxemburg: Louxembourg (city)
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- Sweden: Stockholm
- Turkey: Ankara
- United Kingdom: London