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Overview

To train a machine learning model with Azure Machine Learning, you need to make data available and configure the necessary compute. After training your model and tracking model metrics with MLflow, you can decide to deploy your model to an online endpoint for real-time predictions. Throughout this learning path, you explore how to set up your Azure Machine Learning workspace, after which you train and deploy a machine learning model.
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What You'll Learn

  • 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.
  • 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.
  • Log models with MLflow.
  • Understand the MLmodel format.
  • Register an MLflow model in Azure Machine Learning.
  • 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.

Who Should Attend

N/A
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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...

1. Make data available in Azure Machine Learning

Learn about how to connect to data from the Azure Machine Learning workspace. You're introduced to datastores and data assets.

Click here to know more

2. Work with compute targets in Azure Machine Learning

Learn how to work with compute targets in Azure Machine Learning. Compute targets allow you to run your machine learning workloads. Explore how and when you can use a compute instance or compute cluster.

Click here to know more

3. Work with environments in Azure Machine Learning

Learn how to use environments in Azure Machine Learning to run scripts on any compute target.

Click here to know more

4. Run a training script as a command job in Azure Machine Learning

Learn how to convert your code to a script and run it as a command job in Azure Machine Learning.

Click here to know more

5. Track model training with MLflow in jobs

Learn how to track model training with MLflow in jobs when running scripts.

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6. Register an MLflow model in Azure Machine Learning

Learn how to log and register an MLflow model in Azure Machine Learning.

Click here to know more

7. Deploy a model to a managed online endpoint

Learn how to deploy models to a managed online endpoint for real-time inferencing.

Click here to know more

Frequently Asked Questions (FAQs)

  • Why get Microsoft certified?

    Microsoft certifications validate your skills and expertise in Microsoft technologies and solutions, demonstrating your ability to design, implement, and manage cutting-edge technologies.

    These certifications are globally recognized and highly sought after by employers, as they signify your proficiency in using Microsoft products and services to drive innovation and solve business challenges.

    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?

    Most Microsoft role-based and specialty certifications are valid for one year from the date of passing the exam.

    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.

  • Why take this course with Trainocate?

    Here’s what sets us apart:

    - Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 16 countries (and counting!).

    - Top-Rated Instructors: Our team of subject matter experts (with high average CSAT and MTM scores) are passionate to help you accelerate your digital transformation.

    - Customized Training Solutions: Choose from on-site, virtual classrooms, or self-paced learning to fit your organization and individual needs.

    - Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.

    - Learn From The Best: With 30+ authorized training partnerships and countless awards from Microsoft, AWS, Google – you're guaranteed learning from the industry's elite.

    - Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.

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