Question #1
For a machine learning progress, how should you split data for training and evaluation?
A. Use features for training and labels for evaluation.
B. Randomly split the data into rows for training and rows for evaluation.
C. Use labels for training and features for evaluation.
D. Randomly split the data into columns for training and columns for evaluation.
Correct Answer: B
Question #2
HOTSPOT –
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Hot Area:
Correct Answer:
Question #3
You are building an AI system.
Which task should you include to ensure that the service meets the Microsoft transparency principle for responsible AI?
A. Ensure that all visuals have an associated text that can be read by a screen reader.
B. Enable autoscaling to ensure that a service scales based on demand.
C. Provide documentation to help developers debug code.
D. Ensure that a training dataset is representative of the population.
Correct Answer: C
Question 4
You run a charity event that involves posting photos of people wearing sunglasses on Twitter.
You need to ensure that you only retweet photos that meet the following requirements:
✑ Include one or more faces.
✑ Contain at least one person wearing sunglasses.
What should you use to analyze the images?
A. the Verify operation in the Face service
B. the Detect operation in the Face service
C. the Describe Image operation in the Computer Vision service
D. the Analyze Image operation in the Computer Vision service
Correct Answer: B
Question # 5
DRAG DROP –
You plan to deploy an Azure Machine Learning model as a service that will be used by client applications.
Which three processes should you perform in sequence before you deploy the model? To answer, move the appropriate processes from the list of processes to the answer area and arrange them in the correct order.
Select and Place:
Correct Answer:
Question #6
DRAG DROP –
Match the types of AI workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Select and Place:
Correct Answer:
Question #7
You need to predict the sea level in meters for the next 10 years.
Which type of machine learning should you use?
A. classification
B. regression
C. clustering
Correct Answer: B
Question 8
Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?
A. Form Recognizer
B. Text Analytics
C. Language Understanding
D. Custom Vision
Correct Answer: A
Question # 9
HOTSPOT –
You have the following dataset.
You plan to use the dataset to train a model that will predict the house price categories of houses.
What are Household Income and House Price Category? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
Correct Answer:
Question # 10
You need to predict the income range of a given customer by using the following dataset.
Which two fields should you use as features? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. Education Level
B. Last Name
C. Age
D. Income Range
E. First Name
Correct Answer: AC
Question # 11
What are two metrics that you can use to evaluate a regression model? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. coefficient of determination (R2)
B. F1 score
C. root mean squared error (RMSE)
D. area under curve (AUC)
E. balanced accuracy
Correct Answer: AC
Question # 12
HOTSPOT –
To complete the sentence, select the appropriate option in the answer area.
Hot Area:
Correct Answer:
Question # 13
HOTSPOT –
To complete the sentence, select the appropriate option in the answer area.
Hot Area:
Correct Answer:
Question # 14
HOTSPOT –
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Hot Area:
Correct Answer:
Question # 15
HOTSPOT –
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Hot Area:
Correct Answer:
Question #16
HOTSPOT –
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Hot Area:
Correct Answer:
Question # 17
DRAG DROP –
Match the types of computer vision workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once,
more than once, or not at all.
NOTE: Each correct selection is worth one point.
Select and Place:
Correct Answer:
Question # 18
You send an image to a Computer Vision API and receive back the annotated image shown in the exhibit.
Which type of computer vision was used?
A. object detection
B. face detection
C. optical character recognition (OCR)
D. image classification
Correct Answer: A
Question # 19
Which Computer Vision feature can you use to generate automatic captions for digital photographs?
A. Recognize text.
B. Identify the areas of interest.
C. Detect objects.
D. Describe the images.
Correct Answer: D
Question # 20
HOTSPOT –
To complete the sentence, select the appropriate option in the answer area.
Hot Area:
Correct Answer:
