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Python ProgrammingDesigning and implementing a data science solution on Azure
DP-100
Learn new skills and discover the power of Microsoft Azure with step-by-step guidance.
Demand for Cloud Skills
Learn core Azure services and cloud concepts for career success. Start from the basics and progress to cloud expertise.
Hands-On Learning
Understanding Azure allows you to leverage technology to stay ahead of competitors and adapt to market changes.
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Build a solid foundation in cloud computing with Azure and lead in an increasingly digital business landscape.
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Official Courseware
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The DP-100 course is designed for data scientists who want to build, deploy, and manage machine learning solutions on Microsoft Azure.
This course covers the end-to-end process of implementing AI and ML solutions, from data preparation to model training and deployment using Azure Machine Learning.
Learners will gain hands-on experience in using Azure ML services, automating ML workflows, and leveraging cloud-based AI capabilities.
Course : Designing and implementing a data science solution on Azure
Level : Intermediate
Type : Instructor led Live online or Classroom
Length : 4 days
Labs : Included
Practice Test : Included
Data scientists and AI professionals
Machine learning engineers
IT professionals and developers
Anyone preparing for the Microsoft Certified: Azure Data Scientist Associate certification.
Experience with Python programming.
Understanding of data processing and analysis techniques.
Familiarity with cloud computing concepts, particularly Microsoft Azure.
Understand and implement Azure Machine Learning
Train and optimize machine learning models using Azure ML SDK and AutoML.
Deploy and manage models using Azure ML Pipelines
Perform data ingestion, transformation, and feature engineering
Apply MLOps best practices for automating machine learning workflows.
Monitor and troubleshoot deployed models for performance and scalability.
And more
Instructor-led Virtual online live Training.
Weekend Classes
Evening Classes
Weekdays Classes
Course Outline
Module 1: Explore and configure the Azure Machine Learning workspace
Explore Azure Machine Learning workspace resources and assets
Explore developer tools for workspace interaction
Make data available in Azure Machine Learning
Work with compute targets in Azure Machine Learning
Work with environments in Azure Machine Learning
Module 2: Experiment with Azure Machine Learning
Preprocess data and configure featurization
Run an Automated Machine Learning experiment
Evaluate and compare models
Module 3: Optimize model training with Azure Machine Learning
Run atraining script as a command job in Azure Machine Learning
Track model training with MLflow in jobs
Perform hyperparameter tuning with Azure Machine Learning
Run pipelines in Azure Machine Learning
Module 4: Manage and review models in Azure Machine Learning
Register an MLflow model in Azure Machine Learning
Create and explore the Responsible AI dashboard
Machine Learning
Module 5: Deploy and consume models with Azure Machine Learning
Deploy a model to a managed online endpoint
Deploy a model to a batch endpoint
Module 6: Develop generative AI apps in Azure AI Foundry portal
Introduction to Azure AI Foundry
Explore and deploy models from the model catalog in Azure AI Foundry portal
Get started with prompt flow to develop language model apps in the Azure AI Foundry
Build a RAG-based agent with your own data
Fine-tune a language model with Azure AI Foundry
Evaluate the performance of generative AI apps
Responsible generative AI
Hands-on Labs
Lab : Creating an Azure Machine Learning Workspace
Lab : Use Automated Machine Learning
Lab : Use Azure Machine Learning Designer
Lab : Run Experiments
Lab : Train Models
Lab : Work with Data
Lab : Work with Compute
Lab : Create a Pipeline
Lab : Create a Real-time Inferencing Service
Lab : Create a Batch Inferencing Service
Lab : Tune Hyperparameters
Lab : Use Automated Machine Learning from the SDK
Lab : Explore Differential privacy
Lab : Interpret Models
Lab : Detect and Mitigate Unfairness
Lab : Monitor a Model with Application Insights
Lab : Monitor Data Drift
Best Value offer
Official Courseware
Instructor-led live online / Classroom
Flexible Schedule
Course Completion Certification
US$ 2589
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