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Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.

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What You'll Learn

  • Identify your data source and format
  • Choose how to serve data to machine learning workflows
  • Design a data ingestion solution
  • Identify machine learning tasks
  • Choose a service to train a model
  • Choose between compute options
  • Understand how a model will be consumed.
  • Decide whether to deploy your model to a real-time or batch endpoint.
  • Explore an MLOps architecture.
  • Design for monitoring.
  • Design for retraining.
  • Create an Azure Machine Learning workspace.
  • Identify resources and assets.
  • Train models in the workspace.
  • The Azure Machine Learning studio.
  • The Python Software Development Kit (SDK).
  • The Azure Command Line Interface (CLI).
  • Access data by using Uniform Resource Identifiers (URIs).
  • Connect to cloud data sources with datastores.
  • Use data asset to access specific files or folders.
  • Choose the appropriate compute target.
  • Work with compute instances and clusters.
  • Manage installed packages with environments.
  • Understand environments in Azure Machine Learning.
  • Explore and use curated environments.
  • Create and use custom environments.
  • Prepare your data to use AutoML for classification.
  • Configure and run an AutoML experiment.
  • Evaluate and compare models.
  • Configure to use MLflow in notebooks
  • Use MLflow for model tracking in notebooks
  • Convert a notebook to a script.
  • Test scripts in a terminal.
  • Run a script as a command job.
  • Use parameters in a command job.
  • Use MLflow when you run a script as a job.
  • Review metrics, parameters, artifacts, and models from a run.
  • Define a hyperparameter search space.
  • Configure hyperparameter sampling.
  • Select an early-termination policy.
  • Run a sweep job.
  • Create components.
  • Build an Azure Machine Learning pipeline.
  • Run an Azure Machine Learning pipeline.
  • Log models with MLflow.
  • Understand the MLmodel format.
  • Register an MLflow model in Azure Machine Learning.
  • Understand Azure Machine Learning's built-in components for responsible AI.
  • Create a Responsible AI dashboard.
  • Explore a Responsible AI dashboard.
  • Use managed online endpoints.
  • Deploy your MLflow model to a managed online endpoint.
  • Deploy a custom model to a managed online endpoint.
  • Test online endpoints.
  • Create a batch endpoint.
  • Deploy your MLflow model to a batch endpoint.
  • Deploy a custom model to a batch endpoint.
  • Invoke batch endpoints.

Who Should Attend

DP-100T01 course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.

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Prerequisites

Please review the prerequisites listed for each module in the course content and click on the provided links for more information.

Learning Journey

Coming Soon...

Frequently Asked Questions (FAQs)

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    Microsoft-certified professionals are in high demand, opening doors to new career opportunities and higher earning potential.

  • What to expect for the examination?

    Microsoft certification exams are designed to assess your knowledge and skills in specific Microsoft technologies and solutions.

    Exams typically consist of multiple-choice, multiple-select, and case study questions, and some may include lab simulations to evaluate your practical skills.

    Note: Certification requirements and policies may be updated by Microsoft from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • How long is Microsoft certification valid for?

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    To maintain your certification, you will need to renew it annually by passing a free online assessment on Microsoft Learn.

    However, Microsoft Applied Skills credentials and Fundamentals certifications do not expire.

    Note: Certification requirements and policies may be updated by Microsoft from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

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Course Curriculum

Course Curriculum

Training Schedule

Training Schedule

Exam & Certification

Exam & Certification

FAQs

Frequently Asked Questions

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