Microsoft DP-100 : Designing and Implementing a Data Science Solution on Azure

Microsoft DP-100 Exam Syllabus Topics:

Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx

The dream of becoming a highly skilled data scientist can turn into a reality with the help of the Microsoft DP-100 exam. This exam tries to impart an associate-level understanding of data science and machine learning with an aim to generate a skilled workforce of data scientists.

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The demand for the certified professionals is on the increase. As an Azure Data Scientist, you can explore many employment opportunities. So, if you want to boost your career potential, pursuing the Microsoft Certified: Azure Data Scientist Associate certification is the right step. To get this certificate, you have to pass the qualifying exam, which is Microsoft DP-100. With this associate-level certification, you can get the positions, such as a Data Scientist, a Senior Data Scientist, a Data Science Manager, and a Data Science Director. The average salary for these job roles is $135,000 per annum. With advanced experience, the specialists can earn up to $170,000 per year.

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Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions:

Question #1
You manage an Azure Machine Learning workspace and a GitHub repository. The GitHub repository contains a CSV file located at httpsy/raw.githubusercontent.com/account1/repo1/main/doc1/data1.csv. The CSV file includes embedded newlines.
You plan to consume the content of the CSV file in the workspace. The solution must minimize the possibility of misaligned field values when reading the file content.
You need to create a data asset that references the CSV file.
Which data asset configuration values should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Question #2
You have an Azure Machine Learning workspace named WS1.
You plan to use the Responsible Al dashboard to assess MLflow models that you will register in WS1.
You need to identify the library you should use to register the MLflow models.
Which library should you use?

A. mlpy
B. scikit-learn
C. TensorFlow
D. PyTorch

Question #3
You have a dataset that contains over 150 features. You use the dataset to train a Support Vector Machine (SVM) binary classifier.
You need to use the Permutation Feature Importance module in Azure Machine Learning Studio to compute a set of feature importance scores for the dataset.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.

Question #4
You plan to use the Hyperdrive feature of Azure Machine Learning to determine the optimal hyperparameter values when training a model.
You must use Hyperdrive to try combinations of the following hyperparameter values. You must not apply an early termination policy.
learning_rate: any value between 0.001 and 0.1
* batch_size: 16, 32, or 64
You need to configure the sampling method for the Hyperdrive experiment Which two sampling methods can you use? Each correct answer is a complete solution.
NOTE: Each correct selection is worth one point.

A. Grid sampling
B. Random sampling
C. No sampling
D. Bayesian sampling

Question #5
You have an Azure blob container that contains a set of TSV files. The Azure blob container is registered as a datastore for an Azure Machine Learning service workspace. Each TSV file uses the same data schema.
You plan to aggregate data for all of the TSV files together and then register the aggregated data as a dataset in an Azure Machine Learning workspace by using the Azure Machine Learning SDK for Python.
You run the following code.

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

Solutions: