Ways to Getting DP-100 Exam-Ready
The kind of extensive subject matter for the Microsoft DP-100 can be only obtained once the aspirant has access to quality study resources that are in general endorsed by the vendor itself. Overall, Microsoft offers both free and paid training courses to gain demanded expertise for DP-100. When it comes to the gratis learning path, it contains the following self-paced classes:
- Build AI Solutions with Machine Learning - This is the mid-tier class offered for those who want to get themselves familiarized with Azure ML Python SDK that is used for creating organizational-ready AI solutions. Consisting of 14 full-length parts, the training requires you to possess some experience dealing with Python, PyTorch, ML, Scikit-Learn, and Tensorflow.
- Create No-Code Predictive Models with Azure Machine Learning - In all, it’s beginner training that is composed of 4 concise modules that accentuate such technologies as data science, ML, Azure, and AI engineering. To be entitled to access this learning path and entirely apprehend all the details covered here, you are expected to have some skills in navigating the Azure portal.
- Create Machine Learning Model - This is an intermediate-level free training course with 5 modules that details every single fact you should know about ML and its functions, features, and tools. To enroll for this option, it’s advisable that you have some related experience with the Python programming language.
As far as you can see, all these are the best options to consider when free learning resources for the Microsoft DP-100 exam are concerned. Still, there is one paid instructor-led training course as well. It covers the concepts related to Designing & Implementing a Data Science Solution on Azure and is known as Course DP-100T01-A, which is a 3-day long class explaining every bit of the exam domains. In particular, the course imparts in applicants the intermediate knowledge of ML solutions, Python to monitor data preparation & ingestion, and ML frameworks. During the whole training, you’ll get exposed to as many as 10 comprehensive modules that spin around the test objectives. What makes these lessons significant is that they contain labs in the curriculum unlike free self-paced learning, which allows you to develop practical skills that are generally necessary for job-oriented tasks. So, visit the vendor’s website, check whether you comply with the course prerequisites and if you do, enroll in it, and be entirely geared up for the Microsoft DP-100 exam.
Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx
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What is the duration of the DP-100 Exam
- Format: Multiple choices, multiple answers
- Number of Questions: 45-60
- Passing Score: 700/1000
- Length of Examination: 150 minutes
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Microsoft DP-100 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Deploy and retrain models | 10-15% | - Monitor deployed models
|
| Topic 2: Explore data and train models | 35-40% | - Optimize model performance
|
| Topic 3: Design and prepare a machine learning solution | 20-25% | - Design an Azure Machine Learning workspace
|
| Topic 4: Prepare a model for deployment | 20-25% | - Deploy machine learning models
|
Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions:
You manage an Azure Machine Learning workspace named workspace1 with a compute instance named compute1. You connect to compute! by using a terminal window from wofkspace1. You create a file named " requirements.txt " containing Python dependencies to include Jupyler.
You need to add a new Jupyter kernel to compute1.
Which four commands should you use? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Correct Answer:
Explanation:
You use the Azure Machine learning SDK v2 tor Python and notebooks to tram a model. You use Python code to create a compute target, an environment, and a taring script. You need to prepare information to submit a training job.
Which class should you use?
- A. EndpointConnection
- B. command
- C. MLClient
- D. BuildContext
Correct Answer: B 🗳️
You create a training pipeline by using the Azure Machine Learning designer. You need to load data into a machine learning pipeline by using the Import Data component. Which two data sources could you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point
- A. URL via HTTP
- B. Azure Data Lake Storage Gen2
- C. Registered dataset
- D. Azure SQL Database
- E. Azure Blob storage container through a registered datastore
Correct Answer: A,E 🗳️
You manage an Azure Machine Learning workspace That has an Azure Machine Learning datastore.
Data must be loaded from the following sources:
* a credential-less Azure Blob Storage
* an Azure Data Lake Storage (ADLS) Gen 2 which is not a credential-less datastore You need to define the authentication mechanisms to access data in the Azure Machine Learning datastore.
Which data access mechanism should you use? To answer, move the appropriate data access mechanisms to the correct storage types. You may use each data access mechanism once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
You have an Azure subscription named Sub1 that contains an Azure
* a registered MLflow model named Model1
* an online endpoint named Endpoint1
Outbound network connectivity from Endpointl is blocked. You need to deploy ModeM to Endpointl. What should you do first?
- A. In Subl, create a private endpoint
- B. In Workspacel. create a package.
- C. In Workspacel. create a linked service.
- D. In Workspace! create a package.
- E. In Subl, create an Azure Machine Learning registry.
Correct Answer: A 🗳️
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