hero2-desktop.webp

DP-100T01: Designing and Implementing a Data Science Solution on Azure

Intermediar

DP-100T01: Designing and Implementing a Data Science Solution on Azure

Durată: 4 zile

Certificare: Azure Data Scientist Associate

Cui îi este dedicat cursul?

This 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.

Cunoștințe și abilități inițiale

Successful Azure Data Scientists start this role with a fundamental knowledge of cloud computing concepts, and experience in general data science and machine learning tools and techniques.

Specifically:

  • Creating cloud resources in Microsoft Azure.

  • Using Python to explore and visualize data.

  • Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.

  • Working with containersTo gain these prerequisite skills, take the following free online training before attending the course:

Prezentarea cursului

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.

Ce subiecte abordează cursul

Design a data ingestion strategy for machine learning projects

Design a machine learning model training solution

Design a model deployment solution

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

Find the best classification model with Automated Machine Learning

Track model training in Jupyter notebooks with MLflow

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

Track model training with MLflow in jobs

Run pipelines in Azure Machine Learning

Perform hyperparameter tuning with Azure Machine Learning

Deploy a model to a managed online endpoint

Deploy a model to a batch endpoint

Design a data ingestion strategy for machine learning projects

Design a machine learning model training solution

Design a model deployment solution

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

Find the best classification model with Automated Machine Learning

Track model training in Jupyter notebooks with MLflow

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

Track model training with MLflow in jobs

Run pipelines in Azure Machine Learning

Perform hyperparameter tuning with Azure Machine Learning

Deploy a model to a managed online endpoint

Deploy a model to a batch endpoint

 

Ce abilități se dobândesc în urmă cursului

In this Microsoft Official Course you will learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. 

Nu ai găsit ce căutai? Dă-ne un mesaj!

Prin trimiterea acestui formular sunteți de acord cu termenii și condițiile noastre și cu Politica noastră de confidențialitate, care explică modul în care putem colecta, folosi și dezvălui informațiile dumneavoastră personale, inclusiv către terți.