Machine Learning Specialist
Exam Content Guide
Below we provide a list of the objectives that will be tested on the exam.
For more specific details about each objective download the complete exam content guide.
Data Sources (30%)
- Create a project in Model Studio
- Explore the data
- Modify data
- Reduce the dimensionality of the data
- Use the VARIABLE SELECTION node to identify important variables
Building Models (50%)
- Describe key supervised machine learning terms and concepts
- Build models with decision trees and ensemble of trees
- Build models with neural networks
- Build models with support vector machines
- Incorporate externally written code
Model Assessment and Deployment (20%)
- Explain the principles of Model Assessment
- Assess and compare models in Model Studio
- Deploy a model
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