Free Microsoft DP-100 Exam Questions

Question 1

A set of CSV files contains sales records. All the CSV files have the same data schema.

Each CSV file contains the sales record for a particular month and has the filename sales.csv. Each file in

stored in a folder that indicates the month and year when the data was recorded. The folders are in an Azure

blob container for which a datastore has been defined in an Azure Machine Learning workspace. The folders

are organized in a parent folder named sales to create the following hierarchical structure:

At the end of each month, a new folder with that month’s sales file is added to the sales folder.

You plan to use the sales data to train a machine learning model based on the following requirements:

You must define a dataset that loads all of the sales data to date into a structure that can be easily

converted to a dataframe.

You must be able to create experiments that use only data that was created before a specific previous

month, ignoring any data that was added after that month.

You must register the minimum number of datasets possible.

You need to register the sales data as a dataset in Azure Machine Learning service workspace.

What should you do?

A : Create a tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/sales.csv' file every month. Register the dataset with the name sales_dataset each month, replacing theexisting dataset and specifying a tag named month indicating the month and year it was registered. Usethis dataset for all experiments.

B : Create a tabular dataset that references the datastore and specifies the path 'sales/*/sales.csv', register thedataset with the name sales_dataset and a tag named month indicating the month and year it wasregistered, and use this dataset for all experiments.

C : Create a new tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/sales.csv' file every month. Register the dataset with the name sales_dataset_MM-YYYY each monthwith appropriate MM and YYYY values for the month and year. Use the appropriate month-specificdataset for experiments.

D : Create a tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/sales.csv' file. Register the dataset with the name sales_dataset each month as a new version and with atag named month indicating the month and year it was registered. Use this dataset for all experiments,identifying the version to be used based on the month tag as necessary.

Answer: B

Question 2

You write five Python scripts that must be processed in the order specified in Exhibit A – which allows the

same modules to run in parallel, but will wait for modules with dependencies.

You must create an Azure Machine Learning pipeline using the Python SDK, because you want to script to

create the pipeline to be tracked in your version control system. You have created five PythonScriptSteps and

have named the variables to match the module names.

You need to create the pipeline shown. Assume all relevant imports have been done.

Which Python code segment should you use?

A :

B :

C :

D :

Answer: A

Question 3

You have an Azure Machine Learning workspace. You are connecting an Azure Data Lake Storage Gen2 account to the workspace as a data store.

You need to authorize access from the workspace to the Azure Data Lake Storage Gen2 account.

What should you use?

A : rvice principal

B : token

C : naged identity

D : count key

Answer: A

Question 4

You train and register an Azure Machine Learning model You plan to deploy the model to an online endpoint You need to ensure that applications will be able to use the authentication method with a nonexpiring artifact to access the model. Solution: Create a managed online endpoint and set the value of its auth.mode parameter to aml.token. Deploy the model to the online endpoint. Does the solution meet the goal?

A : Yes

B : No

Answer: B

Question 5

You are developing deep learning models to analyze semi-structured, unstructured, and structured data types. You have the following data available for model building: Video recordings of sporting events Transcripts of radio commentary about events Logs from related social media feeds captured during sporting events You need to select an environment for creating the model. Which environment should you use?

A : Azure Cognitive Services

B : Azure Data Lake Analytics

C : Azure HDInsight with Spark MLib

D : Azure Machine Learning Studio

Answer: A