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Data science without a Ph.D. Using IBM SPSS Modeler (v18.1.1)
This course focuses on reviewing concepts of data science, where participants will learn the stages of a data science project. Topics include using automated tools to prepare data for analysis, build models, evaluate models, and deploy models. To learn about these data science concepts and topics, participants will use IBM SPSS Modeler as a tool.
- Introduction to data science and IBM SPSS Modeler
- Setting measurement levels
- Exploring the data
- Using automated data preparation
- Partitioning the data
- Selecting predictors
- Using automated modeling
- Evaluating models
- Deploying models
• Business Analysts
• Data Scientists
• Participants who want to get started with data science
• It is recommended that you have an understanding of your business data
1: Introduction to data science and IBM SPSS Modeler
• Explain the stages in a data-science project, using the CRISP-DM methodology
• Create IBM SPSS Modeler streams
• Build and apply a machine learning model
2: Setting measurement levels
• Explain the concept of 'field measurement level'
• Explain the consequences of incorrect measurement levels
• Modify a field's measurement level
3: Exploring the data
• Audit the data
• Check for invalid values
• Take action for invalid values
• Impute missing values
• Replace outliers and extremes
4: Using automated data preparation
• Automatically exclude low quality fields
• Automatically replace missing values
• Automatically replace outliers and extremes
5: Partitioning the data
• Explain the rationale for partitioning the data
• Partition the data into a training set and testing set
6: Selecting predictors
• Automatically select important predictors (features) to predict a target
• Explain the limitations of automatically selecting features
7: Using automated modeling
• Find the best model for categorical targets
• Find the best model for continuous targets
• Explain what an ensemble model is
8: Evaluating models
• Evaluate models for categorical targets
• Evaluate models for continuous targets
9: Deploying models
• List two ways to deploy models
• Export scored data
- Duration: 8 Hours
- Delivery Format: Self-Paced Training
- Price: 525.00 USD
- Duration: 8 Hours
- Delivery Format: Classroom Training, Online Training
- Price: 815.00 USD
Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
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Self-Paced Training Terms & Conditions
THIS IS A SELF-PACED VIRTUAL CLASS. AFTER YOU REGISTER, YOU HAVE 30 DAYS TO COMPLETE THE COURSE.
This is a Self-Paced virtual class; it is intended for students who do not need the support of a classroom instructor. If you feel you would better benefit from having access to a Subject Matter Expert, please enroll in the Instructor-Led version instead. Minimal technical support is provided to address issues with accessing the platform or problems within the lab environment.
Before you enroll, review the system requirements to ensure that your system meets the minimum requirements for this course. AFTER YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT. You are billed for the course when you submit the enrollment form. Self-Paced Virtual Classes are non-refundable. Once you purchase a Self-Paced Virtual Class, you will be charged the full price.
After you receive confirmation that you are enrolled, you will be sent further instructions to access your course material and remote labs. A confirmation email will contain your online link, your ID and password, and additional instructions for starting the course.
You can start the course at any time within 12 months of enrolling for the course. After you register/start the course, you have 30 days to complete your course. Within this 30 days, the self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day.
If the course requires a remote lab system, the lab system access is allocated on a first-come, first-served basis. When you are not using the elab system, ensure that you suspend your elab to maximize your hours available to use the elab system.
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