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SASInstitute A00-406 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Sources | 30-36% | - Exploring and modifying data - Importing and preparing data - Dimensionality reduction and feature engineering |
| Topic 2: Model Assessment and Deployment | 24-30% | - Assessing model performance (metrics, ROC curves, confusion matrices) - Deploying models into production |
| Topic 3: Building Models | 40-46% | - Model comparison and selection - Supervised model creation (decision trees, ensembles, SVM, neural networks) |
SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
What is the primary goal of A/B testing in the context of model deployment?
- A. To assess data quality
- B. To compare two different versions of a model or strategy to determine which performs better
- C. To evaluate the model's accuracy
- D. To create synthetic data
Correct Answer: B 🗳️
What is feature engineering in the context of machine learning pipelines?
- A. Testing the model's performance
- B. Applying the model to new data
- C. Building a machine learning model from scratch
- D. Creating new features from existing data
Correct Answer: D 🗳️
In the context of data sources, what is meant by data versioning?
- A. Storing multiple copies of the same data to increase redundancy
- B. Encrypting data to protect against unauthorized access
- C. Compressing data to reduce storage space
- D. Keeping track of different versions or changes to data over time
Correct Answer: D 🗳️
What is the primary purpose of a supervised machine learning pipeline in SAS Viya?
- A. Model training and evaluation
- B. Data preprocessing and cleaning
- C. Data visualization
- D. Data storage and retrieval
Correct Answer: A 🗳️
What is the main advantage of using a RESTful API (Representational State Transfer) as a data source?
- A. Support for complex data structures
- B. High security features
- C. Real-time data processing
- D. Simple and standardized communication
Correct Answer: D 🗳️
