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To prepare for the A00-405 exam, you should have a solid understanding of SAS Viya 3.5 and its various features. You should be familiar with the SAS programming language and have experience in working with unstructured data. A00-405 exam consists of multiple-choice questions and requires you to demonstrate your knowledge of natural language processing and computer vision concepts as well as your ability to implement solutions using SAS Viya 3.5.

SASInstitute A00-405 exam is an industry-recognized certification that focuses on SAS Viya 3.5 Natural Language Processing and Computer Vision. A00-405 exam is designed for professionals who are responsible for developing, implementing, or managing natural language processing and computer vision solutions using SAS Viya 3.5. It is an advanced-level exam that tests the candidate’s ability to design, develop, and deploy machine learning models that can process unstructured data such as text, image, and audio.

Reference: https://www.sas.com/en_ph/certification/exam-content-guides/natural-language-computer-vision-specialist.html

SASInstitute A00-405 certification exam is divided into two parts: a written exam and a practical exam. The written exam comprises 70 multiple-choice questions that test the candidate's theoretical knowledge of the SAS Viya platform and its applications for NLP and CV. The practical exam tests the candidate's practical skills by giving them real-world problems and evaluating their ability to solve them using SAS Viya techniques. Obtaining the SASInstitute A00-405 certification documents your expertise in NLP and CV, providing opportunities for advancement in your career as an analytics professional.

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SASInstitute A00-405 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Identifying Image Patterns Using Computer Vision Techniques38%- Explain the impact of various architectural designs
- Use padding in a Convolutional Neural Network (CNN)
- Use regularization techniques
- Tune the hyperparameters of a Convolutional Neural Network (CNN)
- Use output layers in a Convolutional Neural Network (CNN)
- Use fully connected layers in a Convolutional Neural Network (CNN)
- Use pooling in a Convolutional Neural Network (CNN)
- Use convolutional layers in a Convolutional Neural Network (CNN)
- Score new image data
Topic 2: Loading and Exploring Data20%- Load and prepare image data
- Import documents for analysis
- Create and explore a project in SAS Visual Text Analytics
Topic 3: Identifying Text Patterns Using Natural Language Processing Techniques42%- Use rules to identify documents belonging to specific categories
- Use the Topics Node to extract machine-generated topics
- Write concept rules
- Use a Recurrent Neural Network (RNN) to recognize patterns
- Write category rules
- Use the Concepts and Text Parsing Nodes to extract terms and concepts

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