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Microsoft DP-100 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Optimize language models for AI applications25-30%- Optimize with Retrieval Augmented Generation
  • 1. Configure Azure AI Search
  • 2. Create vector stores and indexes
  • 3. Prepare and process data
- Evaluate and improve models
  • 1. Apply responsible generative AI
  • 2. Optimize for accuracy and safety
  • 3. Test and evaluate responses
- Implement generative AI solutions
  • 1. Apply prompt engineering
  • 2. Build prompt flows
  • 3. Use Azure AI Foundry
Topic 2: Train and deploy models25-30%- Monitor and maintain models
  • 1. Update and retrain models
  • 2. Implement MLOps practices
  • 3. Monitor performance and data drift
- Manage models
  • 1. Register and version models
  • 2. Interpret models and explain predictions
  • 3. Package and validate models
- Deploy models
  • 1. Secure endpoints and manage access
  • 2. Configure compute and scaling
  • 3. Deploy to online endpoints
  • 4. Deploy to batch endpoints
- Train models
  • 1. Use HyperDrive for hyperparameter tuning
  • 2. Apply responsible AI principles
  • 3. Run training scripts
  • 4. Configure jobs and environments
Topic 3: Explore data and run experiments20-25%- Run experiments
  • 1. Use automated machine learning
  • 2. Define parameters and configurations
  • 3. Track runs with MLflow
  • 4. Configure experiment runs
- Explore and visualize data
  • 1. Detect anomalies and outliers
  • 2. Profile and validate data
  • 3. Identify features and relationships
- Implement pipelines
  • 1. Pass data between steps
  • 2. Build reusable components
  • 3. Create and publish pipelines
  • 4. Schedule and monitor pipelines
Topic 4: Design and prepare a machine learning solution20-25%- Manage data assets
  • 1. Select storage services
  • 2. Create and maintain data assets
  • 3. Register and manage datastores
- Manage Azure Machine Learning workspace
  • 1. Create and configure workspace
  • 2. Work with registries
  • 3. Set up Git integration
  • 4. Use developer tools and CLI
- Manage compute resources
  • 1. Attach and monitor compute
  • 2. Create and configure compute targets
  • 3. Select environments
- Design a machine learning solution
  • 1. Define compute specifications for workloads
  • 2. Determine dataset structure and format
  • 3. Select development approach
  • 4. Plan model deployment requirements

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Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q521-Q526):

NEW QUESTION # 521
You are implementing hyperparameter tuning for a model training from a notebook. The notebook is in an Azure Machine Learning workspace. You add code that imports all relevant Python libraries.
You must configure Bayesian sampling over the search space for the num_hidden_layers and batch_size hyperparameters.
You need to complete the following Python code to configure Bayesian sampling.
Which code segments should you use? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.

Answer:

Explanation:
see the answer below.
Explanation
See below image


NEW QUESTION # 522
You are working on a classification task. You have a dataset indicating whether a student would like to play soccer and associated attributes. The dataset includes the following columns:
You need to classify variables by type.
Which variable should you add to each category? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://www.edureka.co/blog/classification-algorithms/


NEW QUESTION # 523
You are the owner of an Azure Machine Learning workspace.
You must prevent the creation or deletion of compute resources by using a custom role. You must allow all other operations inside the workspace.
You need to configure the custom role.
How should you complete the configuration? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


Reference:
https://docs.microsoft.com/en-us/azure/role-based-access-control/overview#how-azure-rbac-determines-if-a-user-has-access-to-a-resource


NEW QUESTION # 524
You use Azure Machine Learning to deploy a model as a real-time web service.
You need to create an entry script for the service that ensures that the model is loaded when the service starts and is used to score new data as it is received.
Which functions should you include in the script? To answer, drag the appropriate functions to the correct actions. Each function 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.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-existing-model


NEW QUESTION # 525
You are performing a filter based feature selection for a dataset 10 build a multi class classifies by using Azure Machine Learning Studio.
The dataset contains categorical features that are highly correlated to the output label column.
You need to select the appropriate feature scoring statistical method to identify the key predictors.
Which method should you use?

Answer: D

Explanation:
Pearson's correlation statistic, or Pearson's correlation coefficient, is also known in statistical models as the r value. For any two variables, it returns a value that indicates the strength of the correlation Pearson's correlation coefficient is the test statistics that measures the statistical relationship, or association, between two continuous variables. It is known as the best method of measuring the association between variables of interest because it is based on the method of covariance. It gives information about the magnitude of the association, or correlation, as well as the direction of the relationship.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/filter-based-feature-selection
https://www.statisticssolutions.com/pearsons-correlation-coefficient/


NEW QUESTION # 526
......

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