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  • Description
  • Content
  • Target Audience
  • Certificates

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.

LEARNING PATH
Train and deploy a machine learning model with Azure Machine Learning

 

 

  • Module 1: Make data available in Azure Machine Learning
  • Module 2: Work with compute targets in Azure Machine Learning
  • Module 3: Work with environments in Azure Machine Learning
  • Module 4: Run a training script as a command job in Azure Machine Learning
  • Module 5: Track model training with MLflow in jobs
  • Module 6: Register an MLflow model in Azure Machine Learning
  • Module 7: Deploy a model to a managed online endpoint

Prerequisites:

none

Applied Skills Assessment – Train and deploy a machine learning model with Azure Machine Learning

Description

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.

Content

LEARNING PATH
Train and deploy a machine learning model with Azure Machine Learning

 

 

  • Module 1: Make data available in Azure Machine Learning
  • Module 2: Work with compute targets in Azure Machine Learning
  • Module 3: Work with environments in Azure Machine Learning
  • Module 4: Run a training script as a command job in Azure Machine Learning
  • Module 5: Track model training with MLflow in jobs
  • Module 6: Register an MLflow model in Azure Machine Learning
  • Module 7: Deploy a model to a managed online endpoint
Target Audience

Prerequisites:

none

Certificates

Applied Skills Assessment – Train and deploy a machine learning model with Azure Machine Learning

Our students for us:

  • - Marko Krstevski Microsoft .NET Academy

    Seeking to expand my knowledge, I decided to enroll in Semos Education, where I am gaining the necessary knowledge and experience.

  • - Teodor Markovski Student

    The desire to become a Cloud architect led me to Semos Education. I am thrilled by the positive experiences of former students and the way in which the instructors and Career Center take care of the students.

  • - Viktorija Georgieva Summer Mentorship Program for Python Develope

    The reputation of Semos Education for quality training and the opportunity to learn from experienced instructors played an additional significant role in my decision.

  • - Demjan Anatoli JavaScript Academy

    An IT educational center that has a consistent presence in the market and offers more stable results than others, coupled with a lower price compared to most of the competition, a fact that helped me choose Semos JavaScript Academy as the right choice for my advancement in this field.

Contact

  • Irena Ivanovska Senior Director
    +389 70 246 146 irena@semos.com.mk