- (Exam Topic 1)
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.

Solution:
Box 3: Natural language processing
Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing

Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A

- (Exam Topic 1)
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?

1. A. the Verify operation in the Face service
2. B. the Detect operation in the Face service
3. C. the Describe Image operation in the Computer Vision service
4. D. the Analyze Image operation in the Computer Vision service

Correct Answer: B
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/overview

- (Exam Topic 2)
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.

1. A. Education Level
2. B. Last Name
3. C. Age
4. D. Income Range
5. E. First Name

Correct Answer: AC
First Name, Last Name, Age and Education Level are features. Income range is a label (what you want to predict). First Name and Last Name are irrelevant in that they have no bearing on income. Age and Education level are the features you should use.

- (Exam Topic 2)
Which two components can you drag onto a canvas in Azure Machine Learning designer? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

1. A. dataset
2. B. compute
3. C. pipeline
4. D. module

Correct Answer: AD
You can drag-and-drop datasets and modules onto the canvas. Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer

- (Exam Topic 1)
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Solution:
Box 1: No
Box 2: Yes
Box 3: Yes
Anomaly detection encompasses many important tasks in machine learning: Identifying transactions that are potentially fraudulent.
Learning patterns that indicate that a network intrusion has occurred. Finding abnormal clusters of patients.
Checking values entered into a system. Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/anomaly-detection

Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A