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Exam Designing and Implementing a Data Science Solution on Azure
Number DP-100
File Name Designing and Implementing a Data Science Solution on Azure.testking.DP-100.2020-02-26.4e.62q.vcex
Size 1.74 Mb
Posted February 26, 2020
Downloads 38



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Demo Questions

Question 1
You are developing a hands-on workshop to introduce Docker for Windows to attendees. 
You need to ensure that workshop attendees can install Docker on their devices. 
Which two prerequisite components should attendees install on the devices? Each correct answer presents part of the solution. 
NOTE: Each correct selection is worth one point.

  • A: Microsoft Hardware-Assisted Virtualization Detection Tool
  • B: Kitematic
  • C: BIOS-enabled virtualization
  • D: VirtualBox
  • E: Windows 10 64-bit Professional



Question 2
Your team is building a data engineering and data science development environment. 
The environment must support the following requirements:
support Python and Scala 
compose data storage, movement, and processing services into automated data pipelines 
the same tool should be used for the orchestration of both data engineering and data science 
support workload isolation and interactive workloads 
enable scaling across a cluster of machines 
You need to create the environment. 
What should you do?

  • A: Build the environment in Apache Hive for HDInsight and use Azure Data Factory for orchestration.
  • B: Build the environment in Azure Databricks and use Azure Data Factory for orchestration.
  • C: Build the environment in Apache Spark for HDInsight and use Azure Container Instances for orchestration.
  • D: Build the environment in Azure Databricks and use Azure Container Instances for orchestration.



Question 3
You plan to build a team data science environment. Data for training models in machine learning pipelines will be over 20 GB in size. 
You have the following requirements:
Models must be built using Caffe2 or Chainer frameworks. 
Data scientists must be able to use a data science environment to build the machine learning pipelines and train models on their personal devices in both connected and disconnected network environments. 
Personal devices must support updating machine learning pipelines when connected to a network. 
You need to select a data science environment. 
Which environment should you use?

  • A: Azure Machine Learning Service
  • B: Azure Machine Learning Studio
  • C: Azure Databricks
  • D: Azure Kubernetes Service (AKS)



Question 4
You are implementing a machine learning model to predict stock prices. 
The model uses a PostgreSQL database and requires GPU processing. 
You need to create a virtual machine that is pre-configured with the required tools. 
What should you do?

  • A: Create a Data Science Virtual Machine (DSVM) Windows edition.
  • B: Create a Geo Al Data Science Virtual Machine (Geo-DSVM) Windows edition.
  • C: Create a Deep Learning Virtual Machine (DLVM) Linux edition.
  • D: Create a Deep Learning Virtual Machine (DLVM) Windows edition.



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



Question 6
You must store data in Azure Blob Storage to support Azure Machine Learning. 
You need to transfer the data into Azure Blob Storage. 
What are three possible ways to achieve the goal? Each correct answer presents a complete solution. 
NOTE: Each correct selection is worth one point.

  • A: Bulk Insert SQL Query
  • B: AzCopy
  • C: Python script
  • D: Azure Storage Explorer
  • E: Bulk Copy Program (BCP)



Question 7
You are moving a large dataset from Azure Machine Learning Studio to a Weka environment. 
You need to format the data for the Weka environment. 
Which module should you use?

  • A: Convert to CSV
  • B: Convert to Dataset
  • C: Convert to ARFF
  • D: Convert to SVMLight



Question 8
You plan to create a speech recognition deep learning model. 
The model must support the latest version of Python. 
You need to recommend a deep learning framework for speech recognition to include in the Data Science Virtual Machine (DSVM). 
What should you recommend?

  • A: Rattle
  • B: TensorFlow
  • C: Weka
  • D: Scikit-learn



Question 9
You plan to use a Deep Learning Virtual Machine (DLVM) to train deep learning models using Compute Unified Device Architecture (CUDA) computations. 
You need to configure the DLVM to support CUDA. 
What should you implement?

  • A: Solid State Drives (SSD)
  • B: Computer Processing Unit (CPU) speed increase by using overclocking
  • C: Graphic Processing Unit (GPU)
  • D: High Random Access Memory (RAM) configuration
  • E: Intel Software Guard Extensions (Intel SGX) technology



Question 10
You plan to use a Data Science Virtual Machine (DSVM) with the open source deep learning frameworks Caffe2 and PyTorch. 
You need to select a pre-configured DSVM to support the frameworks. 
What should you create?

  • A: Data Science Virtual Machine for Windows 2012
  • B: Data Science Virtual Machine for Linux (CentOS)
  • C: Geo AI Data Science Virtual Machine with ArcGIS
  • D: Data Science Virtual Machine for Windows 2016
  • E: Data Science Virtual Machine for Linux (Ubuntu)









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