A00-274 Exam Dumps

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Certification Provider:	SASInstitute
Exam Code / Number:	A00-274
Exam Name:	Interactive Model Building using SAS Visual Statistics 8.4 on SAS Viya
Exam Questions:	0
Corresponding Certification:	SASInstitute Certification

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SASInstitute A00-274 exam is a certification test that measures one's abilities in interactive model building using SAS Visual Statistics 8.4 on SAS Viya. A00-274 exam is aimed at individuals who are interested in advancing their knowledge and skills in the field of data analytics using SAS software. Successful completion of the exam proves that the candidate has the necessary skills to use SAS Visual Statistics to build interactive models that can be used to solve real-world business problems.

SASInstitute A00-274 certification exam is a great way to demonstrate your skills in advanced statistical modeling techniques and data visualization using SAS Viya. A00-274 exam covers a wide range of topics, and you will be tested on your ability to use SAS Viya to build interactive models, create visualizations, and deploy models in production environments. To prepare for the exam, SASInstitute recommends that you take the SAS Visual Statistics 8.4: Interactive Model Building course and use other training resources available.

SASInstitute A00-274 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: SAS Visual Statistics Cross-functional Tasks	18%	- Model workflow operations 1. Apply filters and group-by modeling 2. Perform model validation - Data preparation and transformation 1. Filter data used for modeling 2. Create aggregated measures and derived variables 3. Prepare data using SAS Visual Analytics
Topic 2: Building and Assessing Regression-type Models	40%	- Model assessment 1. ROC, lift, KS statistics 2. Residual analysis and fit statistics - Linear regression modeling 1. Model specification and effects 2. Model diagnostics and interpretation - Logistic regression modeling 1. Binary and multinomial logistic regression 2. Link functions and variable selection
Topic 3: Model Comparison and Scoring	9%	- Model comparison 1. Assessment panel evaluation 2. Champion model selection - Scoring models 1. Score code generation 2. Deploying scoring models
Topic 4: Building and Assessing Segmentation Models	32%	- Unsupervised segmentation 1. Cluster interpretation and evaluation 2. K-means clustering - Decision tree modeling 1. Leaf analysis and interpretation 2. Tree construction and pruning