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What you’ll learn:
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Azure DP-100 Warum-Up – 60 Questions
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Azure DP-100 Exam Preparation – 60 Questions
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Azure DP-100 Exam Preparation – 60 Questions
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Azure DP-100 Exam Preparation – 60 Questions
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Azure DP-100 Exam Preparation – 60 Questions
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Azure DP-100 Exam Preparation – 43 Questions
Description:
Looking for an perfect Azure DP-100 exam preparation? Searching since hours without good results? Congratulation!
You found what you need, without wasting time downloading a lot of stuff you need to sort anyway or which have wrong solutions!
You get an explanation whereever needed, so you don’t need to begin research on your own.
The answers to the questions are validated.
Microsoft Certified: Azure Data Scientist Associate – Full exam preparation
Real exam details:
Duration: 180 Minutes, No. Of Questions: 40-60, Passing Score: 70%.
This course provides overall 340 unique questions for your Azure exam preparation!
We always want to deliver highest quality to you and we made our best to do so. If you find any issue let me know and we will correct it immediatelly 🙂
Well performing Azure practitioners have great long-term job oppertunities. Each higher level of Oracle certification brings a higher standard of benchmarking skill and ability, which leads to greater opportunities and higher pay.
What people say who are certified by Microsoft Azure:
- 23 percent received up to a 20 percent salary increase after obtaining certification
- Nearly 65 percent of respondents received a positive impact on their professional image or reputation after obtaining certification
- 54 percent of those who obtained certifications experienced a career benefit within three months, and 24 percent experienced the benefit immediately.
Benefeits of getting further certified:
- Added credibility
- Good job opportunities
- Azure Experts are in Demand
- More than 80 percent of Fortune 500 companies are taking advantage of Microsoft Cloud
- Data shows that around 90 percent of companies are taking some advantage of cloud technology
Exam Concepts:
- Manage Azure resources for machine learning(25-30%)
- Run experiments and train models (20-25%)
- Deploy and operationalize machine learning solutions (35-40%)
- Implement responsible machine learning (5-10%)
This course provide overall 540 unique questions for your exam preparation. There are no duplicated questions. All questions are multiple choice with one or several correct answer. You will get the information of how many answers are correct for each question as in the real exam.
There are 5 test exams for you. Each has 60 questions as the real exam has.
There sixth exam test contains 240 questions. You should do this test, after solving the first 5 tests with a very good score
Run experiments and train models (20-25%)
- Create models by using the Azure Machine Learning designer
- create a training pipeline by using Azure Machine Learning designer
- ingest data in a designer pipeline
- use designer modules to define a pipeline data flow
- use custom code modules in designer
- Run model training scripts
- create and run an experiment by using the Azure Machine Learning SDK
- configure run settings for a script
- consume data from a dataset in an experiment by using the Azure Machine Learning
- SDK
- run a training script on Azure Databricks compute
- run code to train a model in an Azure Databricks notebook
- Generate metrics from an experiment run
- log metrics from an experiment run
- retrieve and view experiment outputs
- use logs to troubleshoot experiment run errors
- use MLflow to track experiments
- track experiments running in Azure Databricks
- Use Automated Machine Learning to create optimal models
- use the Automated ML interface in Azure Machine Learning studio
- use Automated ML from the Azure Machine Learning SDK
- select pre-processing options
- select the algorithms to be searched
- define a primary metric
- get data for an Automated ML run
- retrieve the best model
- Tune hyperparameters with Azure Machine Learning
- select a sampling method
- define the search space
- define the primary metric
- define early termination options
- find the model that has optimal hyperparameter values
Deploy and operationalize machine learning solutions (35-40%)
- Select compute for model deployment
- consider security for deployed services
- evaluate compute options for deployment
- Deploy a model as a service
- configure deployment settings
- deploy a registered model
- deploy a model trained in Azure Databricks to an Azure Machine Learning endpoint
- consume a deployed service
- troubleshoot deployment container issues
- Manage models in Azure Machine Learning
- register a trained model
- monitor model usage
- monitor data drift
- Create an Azure Machine Learning pipeline for batch inferencing
- configure a ParallelRunStep
- configure compute for a batch inferencing pipeline
- publish a batch inferencing pipeline
- run a batch inferencing pipeline and obtain outputs
- obtain outputs from a ParallelRunStep
- Publish an Azure Machine Learning designer pipeline as a web service
- create a target compute resource
- configure an inference pipeline
- consume a deployed endpoint
- Implement pipelines by using the Azure Machine Learning SDK
Who this course is for:
- DP-100
- Azure
- Exam preparation
- Certification
- Machine Learning
- Data Science
- AI
- Microsoft
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