Practice Free AI-900 Exam Online Questions
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.
Explanation:
A bot that responds to queries by internal users is an example of a conversational AI workload.
Yes, a bot responding to queries is essentially engaging in a conversation with users, making it a conversational AI workload.
An application that displays images relating to an entered search term is an example of a conversational AI workload.
No, while this involves user interaction, it doesn’t involve natural language conversation. It’s more of a search and retrieval workload.
A web form used to submit a request to reset a password is an example of a conversational AI workload.
No, a web form for password reset is a user interface element that captures user input, but it doesn’t engage in natural language conversation with the user.
DRAG DROP
You need to use Azure Machine Learning designer to build a model that will predict automobile prices.
Which type of modules should you use to complete the model? To answer, drag the appropriate modules to the correct locations. Each module may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.
Explanation:
Diagram
Description automatically generated
Box 1: Select Columns in Dataset
For Columns to be cleaned, choose the columns that contain the missing values you want to change. You can choose multiple columns, but you must use the same replacement method in all selected columns.
Example:
Box 2: Split data
Splitting data is a common task in machine learning. You will split your data into two separate datasets. One dataset will train the model and the other will test how well the model performed.
Box 3: Linear regression
Because you want to predict price, which is a number, you can use a regression algorithm.
For this example, you use a linear regression model.
You build a machine learning model by using the automated machine learning user interface (UI).
You need to ensure that the model meets the Microsoft transparency principle for responsible AI.
What should you do?
- A . Set Validation type to Auto.
- B . Enable Explain best model.
- C . Set Primary metric to accuracy.
- D . Set Max concurrent iterations to 0.
B
Explanation:
Model Explain Ability.
Most businesses run on trust and being able to open the ML “black box” helps build transparency and trust. In heavily regulated industries like healthcare and banking, it is critical to comply with regulations and best practices. One key aspect of this is understanding the relationship between input variables (features) and model output. Knowing both the magnitude and direction of the impact each feature (feature importance) has on the predicted value helps better understand and explain the model. With model explain ability, we enable you to understand feature importance as part of automated ML runs.
Reference: https://azure.microsoft.com/en-us/blog/new-automated-machine-learning-capabilities-in-azure-machine-learning-service/
You need to provide content for a business chatbot that will help answer simple user queries.
What are three ways to create question and answer text by using QnA Maker? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
- A . Generate the questions and answers from an existing webpage.
- B . Use automated machine learning to train a model based on a file that contains the questions.
- C . Manually enter the questions and answers.
- D . Connect the bot to the Cortana channel and ask questions by using Cortana.
- E . Import chit-chat content from a predefined data source.
A,C,E
Explanation:
Automatic extraction
Extract question-answer pairs from semi-structured content, including FAQ pages, support websites, excel files, SharePoint documents, product manuals and policies.
Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/content-types
A company employs a team of customer service agents to provide telephone and email support to customers.
The company develops a webchat bot to provide automated answers to common customer queries.
Which business benefit should the company expect as a result of creating the webchat bot solution?
- A . increased sales
- B . a reduced workload for the customer service agents
- C . improved product reliability
In which two scenarios can you use a speech synthesis solution? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
- A . an automated voice that reads back a credit card number entered into a telephone by using a numeric keypad
- B . generating live captions for a news broadcast
- C . extracting key phrases from the audio recording of a meeting
- D . an Al character in a computer game that speaks audibly to a player
A,D
Explanation:
Azure Text to Speech is a Speech service feature that converts text to lifelike speech.
Reference: https://azure.microsoft.com/en-in/services/cognitive-services/text-to-speech/
You are building an Al-based loan approval app.
You need to ensure that the app documents why a loan is approved or rejected and makes the report available to the applicant.
This is an example of which Microsoft responsible Al principle?
- A . fairness
- B . inclusiveness
- C . transparency
- D . accountability
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.
Explanation:
Providing an explanation of the outcome of a credit loan application is an example of the Microsoft transparency principle for responsible AI.
Yes, transparency involves making the operation and outcomes of AI models clear and understandable. Providing explanations for credit loan outcomes aligns with this principle.
A triage bot that prioritizes insurance claims based on injuries is an example of the Microsoft reliability and safety principle for responsible AI.
Yes, reliability and safety involve ensuring that AI systems operate reliably and safely, prioritizing urgent cases like severe injuries aligns with this principle.
An AI solution that is offered at different prices for different sales territories is an example of the Microsoft inclusiveness principle for responsible AI.
No, inclusiveness involves ensuring that AI systems are accessible and usable by as many people as possible, and offering AI solutions at different prices doesn’t necessarily align with this principle.
Which type of natural language processing (NLP) entity is used to identify a phone number?
- A . regular expression
- B . machine-learned
- C . list
- D . Pattern-any
Stating the source of the data used to train a model is an example of which responsible Al principle?
- A . fairness
- B . transparency
- C . reliability and safety
- D . privacy and security