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Exam Code: A00-405
Exam Name: SAS Viya 3.5 Natural Language Processing and Computer Vision
Updated: Jul 21, 2026
Q & A: 62 Questions and Answers
A00-405 Free Demo download
SASInstitute A00-405 exam is designed to test the knowledge and skills of professionals in using SAS Viya 3.5 for natural language processing and computer vision. A00-405 exam covers various topics such as text analytics, sentiment analysis, image analysis, and machine learning algorithms. A00-405 exam also includes questions on SAS Viya 3.5 architecture and deployment, data preparation and management, and model deployment and monitoring.
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SASInstitute A00-405 certification exam is designed for professionals who want to validate their skills and knowledge in Natural Language Processing (NLP) and Computer Vision using SAS Viya 3.5. A00-405 exam covers a wide range of topics, including data preparation, feature engineering, model building, and evaluation. To pass the exam, candidates must demonstrate their ability to use SAS Viya to solve real-world problems related to NLP and Computer Vision.
SASInstitute A00-405 exam consists of 65 multiple-choice questions that must be completed within 2 hours and 15 minutes. A00-405 exam is available in English and is delivered through Pearson VUE. Candidates who pass the exam will receive a SAS Certified Specialist: Viya 3.5 Natural Language Processing and Computer Vision certificate.
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Loading and Exploring Data | 20% | - Load and prepare image data - Create and explore a project in SAS Visual Text Analytics - Import documents for analysis |
| Topic 2: Identifying Text Patterns Using Natural Language Processing Techniques | 42% | - Use the Concepts and Text Parsing Nodes to extract terms and concepts - Use a Recurrent Neural Network (RNN) to recognize patterns - Write concept rules - Use the Topics Node to extract machine-generated topics - Use rules to identify documents belonging to specific categories - Write category rules |
| Topic 3: Identifying Image Patterns Using Computer Vision Techniques | 38% | - Explain the impact of various architectural designs - Tune the hyperparameters of a Convolutional Neural Network (CNN) - Use convolutional layers in a Convolutional Neural Network (CNN) - Use fully connected layers in a Convolutional Neural Network (CNN) - Score new image data - Use pooling in a Convolutional Neural Network (CNN) - Use output layers in a Convolutional Neural Network (CNN) - Use regularization techniques - Use padding in a Convolutional Neural Network (CNN) |
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