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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Data Science Solution on Azure |
| Exam Number: | DP-100 |
| Related Certifications: | Microsoft Certified: Azure Data Scientist Associate |
| Passing Score: | 700/1000 |
| Available Languages: | Simplified Chinese, Portuguese (Brazil), Korean, German, English, Japanese, Spanish, French, Russian |
| Exam Price: | USD 165 (varies by region) |
| Real Exam Qty: | 40-60 |
| Exam Duration: | 100-120 |
| Exam Format: | Multiple response, Case studies, Multiple choice, Drag and drop, Hands-on lab tasks |
| Certificate Validity Period: | 1 year (renewable through Microsoft certification renewal assessment) |
| Recommended Training: | Microsoft Learn - DP-100 Learning Path Azure Machine Learning Documentation |
| Exam Registration: | Official Microsoft Certification Page Pearson VUE Registration |
| Sample Questions: | Microsoft DP-100 Sample Questions |
| Exam Way: | Online proctored or in-person at authorized testing centers (Pearson VUE) |
| Pre Condition: | No mandatory prerequisites. Recommended familiarity with Python, machine learning concepts, and Azure fundamentals. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-data-scientist/ |
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The DP-100 exam covers various topics related to data science, including designing and implementing data ingestion and processing solutions, designing and implementing machine learning models, designing and implementing data storage solutions, and designing and implementing data visualization solutions. DP-100 exam also evaluates the candidate's knowledge of Azure services such as Azure Machine Learning, Azure Databricks, Azure Stream Analytics, and Azure Data Factory.
These are following steps for registering the DP-100 Exam.Step 1: Visit to Microsoft Exam RegistrationStep 2: Signup/Login to MICROSOFT accountStep 3: Search for MICROSOFT DP-100 Certifications ExamStep 4: Select Date and Center of examination and confirm with payment value of $165
NEW QUESTION # 290
You have a dataset contains 2,000 rows. You arc building a machine learning classification model by using Azure Machine Learning Studio. You add a Partition and Sample module to the experiment.
You need to configure the module. You must meet the following requirements:
* Divide the data into subsets.
* Assign the rows into folds using a round-robin method.
* Allow rows in the dataset to be reused.
How should you configure the module? To answer select the appropriate Options m the dialog box in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 291
You are a data scientist creating a linear regression model.
You need to determine how closely the data fits the regression line.
Which metric should you review?
Answer: A
Explanation:
Coefficient of determination, often referred to as R2, represents the predictive power of the model as a value between 0 and 1. Zero means the model is random (explains nothing); 1 means there is a perfect fit. However, caution should be used in interpreting R2 values, as low values can be entirely normal and high values can be suspect.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate-model
NEW QUESTION # 292
You plan to explore demographic data for home ownership in various cities. The data is in a CSV file with the following format:
age,city,income,home_owner
21,Chicago,50000,0
35,Seattle,120000,1
23,Seattle,65000,0
45,Seattle,130000,1
18,Chicago,48000,0
You need to run an experiment in your Azure Machine Learning workspace to explore the data and log the results. The experiment must log the following information:
the number of observations in the dataset
a box plot of income by home_owner
a dictionary containing the city names and the average income for each city You need to use the appropriate logging methods of the experiment's run object to log the required information.
How should you complete the code? To answer, drag the appropriate code segments to the correct locations. Each code segment 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:
NEW QUESTION # 293
You create an Azure Machine Learning workspace. You are training a classification model with no-code AutoML in Azure Machine Learning studio.
The model must predict if a client of a financial institution will subscribe to a fixed-term deposit. You must preview the data profile in Azure Machine Learning studio once the dataset is created.
You need to train the model.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
1 - Create a file dataset.
2 - Create a compute cluster.
3 - Create an experiment.
4 - Create an automated MLjob.
NEW QUESTION # 294
You create a script that trains a convolutional neural network model over multiple epochs and logs the validation loss after each epoch. The script includes arguments for batch size and learning rate.
You identify a set of batch size and learning rate values that you want to try.
You need to use Azure Machine Learning to find the combination of batch size and learning rate that results in the model with the lowest validation loss.
What should you do?
Answer: D
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
NEW QUESTION # 295
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