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: 0A069G | Category: IBM SPSS Modeler / IBM SPSS Modeler |
| Delivery: Online & on-site** | Course length in days: 2 |
Target audience
- Data scientists
- Business analysts
- Clients who are new to IBM SPSS Modeler or want to find out more about using it
Desired Prerequisites:
- Knowledge of your business requirements
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
Introduction to IBM SPSS Modeler
• Introduction to data science
• Describe the CRISP-DM methodology
• Introduction to IBM SPSS Modeler
• Build models and apply them to new data
Collect initial data
• Describe field storage
• Describe field measurement level
• Import from various data formats
• Export to various data formats
Understand the data
• Audit the data
• Check for invalid values
• Take action for invalid values
• Define blanks
Set the unit of analysis
• Remove duplicates
• Aggregate data
• Transform nominal fields into flags
• Restructure data
Integrate data
• Append datasets
• Merge datasets
• Sample records
Transform fields
• Use the Control Language for Expression Manipulation
• Derive fields
• Reclassify fields
• Bin fields
Further field transformations
• Use functions
• Replace field values
• Transform distributions
Examine relationships
• Examine the relationship between two categorical fields
• Examine the relationship between a categorical and continuous field
• Examine the relationship between two continuous fields
Introduction to modeling
• Describe modeling objectives
• Create supervised models
• Create segmentation models
Improve 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
- Austria: Vienna
- Belgium: Brussels, Ghent
- Denmark: Cophenhagen
- Estonia: Tallinn
- Finland: Helsinki
- France: Paris, Marseille, Lyon
- Germany: Berlin, Munich, Cologne, Hamburg
- Greece: Athens, Thessaloniki
- Italy: Rome
- Louxemburg: Louxembourg (city)
- Netherlands: Amsterdam
- Norway: Oslo
- Portugal: Lisbon, Braga, Porto, Coimbra
- Slovakia: Bratislava
- Slovenia: Bratislava
- Spain: Madrid, Sevilla, Valencia, Barcelona, Bilbao, Málaga
- Sweden: Stockholm
- Turkey: Ankara
- United Kingdom: London
