The Azure Data Scientist applies their knowledge of data science and machine learning to implement and run machine learning workloads on Azure; in particular, using Azure Machine Learning Service. This entails planning and creating a suitable working environment for data science workloads on Azure, running data experiments and training predictive models, managing and optimizing models, and deploying machine learning models into production
About this course
The Azure Data Scientist applies their knowledge of data science and machine learning to implement and run machine learning workloads on Azure; in particular, using Azure Machine Learning Service.
Why should you take this course?
Companies require skilled Data Scientists to process and analyze their data. They not only analyze the data but also improve its quality. Therefore, Data Science deals with enriching data and making it better for their company.
What will you learn by taking this course?
This exam measures the ability to accomplish the tasks such as setting up an Azure Machine Learning workspace; run experiments; train, optimize, manage, deploy, and consume models.
Chapter 1: Set up an Azure Machine Learning Workspace
✅ Create an Azure Machine Learning workspace
✅ Manage data objects in an Azure Machine Learning workspace
✅ Manage experiment compute contexts
Chapter 2: Run Experiments and Train Models
✅ Create models by using Azure Machine Learning Designer
✅ Run training scripts in an Azure Machine Learning workspace
✅ Generate metrics from an experiment run
✅ Automate the model training process
Chapter 3: Optimize and Manage Models
✅ Use Automated ML to create optimal models
✅ Use Hyperdrive to tune hyperparameters
✅ Use model explainers to interpret models
✅ Manage models
Chapter 4: Deploy and Consume Models
✅ Create production compute targets
✅ Deploy a model as a service
✅ Create a pipeline for batch inferencing
✅ Publish a designer pipeline as a web service
What is Azure?
Azure is a cloud computing platform and an online portal that allows access and manage the cloud services and resources provided by Microsoft. The services and resources include storing data and transforming it, depending on user requirements.
What is the major difference between a Data Scientist and an Azure Data Scientist?
Th A data scientist applies machine learning techniques to train, evaluate, and deploy models that can solve business problems whereas an Azure Data Scientist applies its knowledge of data science and machine learning to implement and run machine learning workloads on Azure by using the Azure Machine Learning Service.
What is the level of Python required for the Azure Data Scientist certification?
Since Azure Data Scientist certification and Python is the most widely used and recommended language to work within the data science and machine learning field. So yes if you have basic knowledge of python, commands, libraries, etc it will help in a better understanding of code and concepts of the certification else you can always learn on the way.
What level of mathematical and statistical knowledge we need to have as a prerequisite for the Azure Data Scientist certification?
Basic level of mathematics and statistical concepts knowledge will help in a better understanding of the machine learning model’s evaluation metrics and outcomes.
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