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SAS Certified Specialist (A00-402) Exam Format
Language: English
Exam Length: 50-55 Questions
Passing Score: Must achieve a score of 65 percent correct to pass
Exam Format: Multiple choice and Short-answer questions
Exam Duration: 100 minutes to complete the exam.
Steps to Become SAS Certified Specialist (A00-402) Exam
Candidates working across multiple industries can take up this certification to validate their skills. There are several ways available to become SAS Certified Specialist certified candidate. These include taking paid training courses from a few commercial vendors or enrolling in university programs that are dedicated to preparing students for this certification.
In order to be eligible for the SAS Certified Specialist exam, candidates should have at least 18 months of work experience in SAS programming. The exam is widely accepted in industries such as healthcare and pharmaceuticals, manufacturing, finance and insurance, retail/wholesale distribution, telecommunications, and information technology. Initially designed to cater to the needs of business managers who rely on SAS software for data analysis, the SAS Certified Specialist exam has become popular in other industries as well due to the rapid growth of the IT industry. SAS Institute A00-402 Dumps helps you in becoming a certified.
Candidates can also seek out relevant work experience and directly apply for the certification without any formal training programs. To ensure that candidates fulfill all requirements for getting certified, they are subject to rigorous testing under the supervision of certified trainers who are employed by approved training organizations or
The SAS Certified Specialist certification is a credential that has been designed to assess an individual's ability in using SAS software tools, applications, and procedures. It is a professional-level certification that validates the candidates' expertise in SAS programming.
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SASInstitute A00-402 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Supervised Learning Algorithms | - Tree-based models
|
| Topic 2: Data Preparation for Machine Learning | - Data cleansing and preprocessing in SAS Viya
|
| Topic 3: Model Training and Optimization | - Model training workflows in SAS Viya Model Studio
|
| Topic 4: Model Assessment and Deployment | - Model evaluation
|
