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SASInstitute A00-408 Exam Syllabus Topics:

Section

Weight

Objectives

Loading and Exploring Data

18-22%

- Import Documents for Analysis

1. Minimize information loss when converting proprietary formats
2. Explore and prepare documents
3. Convert documents for analysis
4. Troubleshoot language encoding issues

- Create and Explore a Project in SAS Visual Text Analytics

1. Identify key features of the term table
2. Assign text and category roles
3. Identify the default pipeline
4. Explore the Documents Table
5. Export score code for new data

- Load and Prepare Image Data

1. Load labeled image data
2. Augment image data
3. Prepare image data for modeling

Identifying Text Patterns Using Computer Vision Techniques

35-40%

- Build and Evaluate Deep Learning Models

1. Evaluate model performance
2. Train convolutional neural networks
3. Apply regularization and optimization methods
4. Apply transfer learning techniques
5. Score and classify images

- Prepare and Process Images

1. Apply image preprocessing techniques
2. Load and manage image data
3. Perform image augmentation

Identifying Text Patterns Using Natural Language Processing Techniques

40-45%

- Extract Terms and Concepts

1. Modify the term table and evaluate impact
2. Use include, exclude, and synonym lists
3. Create custom concepts
4. Evaluate concept impact on the pipeline
5. Explore and interpret the term map
6. Use predefined concepts
7. View document matches and similarity scores
8. Explain the value of concepts

- Analyze and Model Text Data

1. Perform text categorization
2. Interpret natural language processing results
3. Identify text patterns
4. Apply text analytics techniques

SASInstitute A00-408 : SAS® Viya® Natural Language Processing and Computer Vision

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SASInstitute A00-408 Exam Syllabus Topics:

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