DP-100T01-A | Designing and Implementing a Data Science Solution on Azure
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 in Microsoft Azure.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.
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.
- 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:
- Explore Microsoft cloud concepts.
- Create machine learning models.
- Administer containers in AzureIf you are completely new to data science and machine learning, please complete Microsoft Azure AI Fundamentals first.
Module 1: Create machine learning models
Microsoft Learn provides several interactive ways to get an introduction to classic machine learning. These learning paths will get you productive on their own, and also are an excellent base for moving on to deep learning topics.
From the most basic classical machine learning models, to exploratory data analysis and customizing architectures, you’ll be guided by easy to digest conceptual content and interactive Jupyter notebooks, all without leaving your browser.
- Explore and analyze data with Python
- Train and evaluate regression models
- Train and evaluate classification models
- Train and evaluate clustering models
- Train and evaluate deep learning models
Module 2: Microsoft Azure AI Fundamentals: Explore visual tools for machine learning
Machine learning is at the core of artificial intelligence, and many modern applications and services depend on predictive machine learning models. Learn how to use Azure Machine Learning to create and publish models without writing code.
- Use Automated Machine Learning in Azure Machine Learning
- Create a regression model with Azure Machine Learning designer
- Create a classification model with Azure Machine Learning designer
- Create a clustering model with Azure Machine Learning designer
Module 3: Build and operate machine learning solutions with Azure Machine Learning
Azure Machine Learning is a cloud platform for training, deploying, managing, and monitoring machine learning models. Learn how to use the Azure Machine Learning Python SDK to create and manage enterprise-ready ML solutions.
- Introduction to the Azure Machine Learning SDK
- Train a machine learning model with Azure Machine Learning
- Work with Data in Azure Machine Learning
- Work with Compute in Azure Machine Learning
- Orchestrate machine learning with pipelines
- Deploy real-time machine learning services with Azure Machine Learning
- Deploy batch inference pipelines with Azure Machine Learning
- Tune hyperparameters with Azure Machine Learning
- Automate machine learning model selection with Azure Machine Learning
- Explore differential privacy
- Explain machine learning models with Azure Machine Learning
- Detect and mitigate unfairness in models with Azure Machine Learning
- Monitor models with Azure Machine Learning
- Monitor data drift with Azure Machine Learning
- Explore security concepts in Azure Machine Learning
Module 4: Build and operate machine learning solutions with Azure Databricks
Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this learning path, you'll learn how to use Azure Databricks to explore, prepare, and model data; and integrate with Azure Machine Learning.
- Get started with Azure Databricks
- Work with data in Azure Databricks
- Prepare data for machine learning with Azure Databricks
- Train a machine learning model with Azure Databricks
- Use MLflow to track experiments in Azure Databricks
- Manage machine learning models in Azure Databricks
- Track Azure Databricks experiments in Azure Machine Learning
- Deploy Azure Databricks models in Azure Machine Learning
- Tune hyperparameters with Azure Databricks
- Distributed deep learning with Horovod and Azure Databricks
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Debido a las constantes actualizaciones de los contenidos de los cursos por parte del fabricante, el contenido de este temario puede variar con respecto al publicado en el sitio oficial, sin embargo, Netec siempre entregará la versión actualizada de éste