FREE Microsoft Azure AI Fundamentals Questions and Answers

Question 1

Which two tasks are carried out during an Azure Machine Learning process's data ingestion and data preparation phases?

Accepted Answer

Combine multiple datasets.

Answer

During the data ingestion and preparation phases of an Azure Machine Learning process, the focus is on collecting and cleaning data. Combining multiple datasets (data integration) is essential for creating a comprehensive dataset, and removing records with missing values (data cleaning) addresses data quality issues. These steps ensure the data is suitable and robust for subsequent model training.

Question 2

An area's animal population needs to be predicted. What kind of Azure Machine Learning should you employ?

Accepted Answer

regression

Answer

Predicting an area's animal population involves forecasting a continuous numerical value (the count of animals). Regression models are specifically designed for tasks where the output is a numerical quantity. Classification is used for predicting discrete categories, and clustering is for grouping data, neither of which fits the requirement of predicting a specific population count.

Question 3

Which two programming languages are supported by the Azure Machine Learning designer?

Accepted Answer

Python

Answer

The Azure Machine Learning designer, while primarily a visual interface, supports custom code execution to extend its capabilities. Python and R are the two most widely adopted programming languages in data science and machine learning. Azure ML provides integrated environments and modules for users to incorporate scripts written in both Python and R into their machine learning pipelines.

Question 4

Your business plans to construct a bottle recycling machine. Bottles with the proper shape must be automatically recognized by the recycling system, while all other objects must be rejected. What kind of AI workload should the business employ?

Accepted Answer

computer vision

Answer

The task of automatically recognizing bottles of a proper shape and rejecting other objects is a classic application of computer vision. Computer vision AI workloads enable systems to 'see,' process, and interpret visual information from images or videos. This capability is crucial for tasks like object recognition, classification, and shape analysis in real-world scenarios.

Question 5

You have a dataset that details taxi trips that took place over a specific time period. In order to estimate the cost of a taxi ride, a model needs to be trained. What kind of feature should you use?

Accepted Answer

the trip distance of individual taxi journeys

Answer

To accurately estimate the cost (fare) of a taxi ride, the model requires features that are highly correlated with the fare. Trip distance is a primary determinant of taxi fare, as longer distances typically incur higher costs. Therefore, the trip distance of individual taxi journeys is a crucial input feature for training such a predictive model.

Microsoft Azure AI Fundamentals Practice Test

Microsoft Azure AI Fundamentals Practice Test

FREE Microsoft Azure AI Fundamentals Questions and Answers