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SAS Viya 3.5 Natural Language Processing and Computer Vision

For data scientists, text and image analysts, AI specialists and others who analyze text and image data to recognize patterns. Successful candidates are familiar with SAS Model Studio for SAS Viya, SAS Visual Text Analytics and SAS Data Mining and Machine Learning . They are skilled in tasks such as: text topic detection, sentiment analysis, image processing, image classification and deep learning with static and dynamic data.

Exam Information

• This exam is administered by SAS and Pearson VUE.
• 60 scored multiple-choice and short-answer questions.
• (Must achieve score of 70 percent correct to pass)
• 110 minutes to complete exam.
• Use exam ID A00-405; required when registering with Pearson VUE.
• This exam is based on SAS Viya 3.5.
• Exam fee: $255 AUD. 
• Candidates who earn this credential will have earned a passing score on the SAS Viya 3.5 Natural Language Processing and Computer Vision exam.

Exam Topics

Loading and Exploring Data (20%)

• Import documents for analysis
• Create and explore a project in SAS Visual Text Analytics
• Load and prepare image data

Identifying Text Patterns Using Natural Language Processing Techniques (42%)

• Use the Concepts and Text Parsing Nodes to extract Terms and Concepts
• Write concept rules
• Use the Topics Node to extract machine-generated topics
• Use rules to identify documents belonging to specific categories
• Write category rules
• Use a Recurrent Neural Network (RNN) to recognize patterns

Identifying Image Patterns Using Computer Vision Techniques (38%)

• Use convolutional layers in a Convolutional Neural Network (CNN)
• Use padding in a Convolutional Neural Network (CNN)
• Use pooling in a Convolutional Neural Network (CNN)
• Use fully connected layers in a Convolutional Neural Network (CNN)
• Use output layers in a Convolutional Neural Network (CNN)
• Tune the Hyperparameters of a Convolutional Neural Network (CNN)
• Score new image data
• Explain the impact of various architectural designs
• Use regularization techniques

View Online SAS Viya 3.5 Natural Language Processing and Computer Vision A00-405 Free Questions

Which statement is TRUE concerning the "dropout" option?
A.It specifies the number of neurons to drop from each layer of the network
B.It specifies the percentage of neurons to drop from a given layer of the network
C.It specifies the percentage of neurons to drop from the entire network
D.It specifies the number of layers to drop from the entire network
Answer:B

Which statement is TRUE about importing documents into SAS Visual Text Analytics using the Explore and Visualize Data menu?
A.You must include your document collection in a parent folder
B.You must convert your document collection to a SAS data set
C.You must correct misspelled words in the document collection
D.You must store the documents as txt files in a folder
Answer:A

Which feature is enabled in the default settings of the Text Parsing Node?
A.minimum number of documents
B.start list
C.synonym list
D.misspelling detection
Answer:D

Regularization in neural networks represents a set of techniques devised to accomplish what?
A.Reduce overfitting
B.Downsample a feature map
C.Minimize the toss function
D.Calculate a softmax
Answer:C

You have a very large set of documents you are preparing for SAS Visual Text Analytics Which two actions should you perform during data preparation? (Choose two)
A.Use CHAR data type tor the Text variable with a long length
B.Have enough number of documents for each category label
C.Sample the data first for subsequent interactive model development
D.Keep all the character variables in addition to the Text variable
Answer:A, C