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

COURSE DESCRIPTION

Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This CertKit 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.

• 12 Months Online Access
• 18+ hours of eLearning
• Measure-Up Exam simulation – 130 questions
• Tips & Tricks

CERTIFICATION

This course prepares participants for the official Microsoft DP-100 exam, which can be taken separately after completing the training. This exam is optional and can be ordered separately with the training course.

LEARNING OUTCOMES

In this course, you will learn to:

• Provision an Azure Machine Learning workspace
• Use tools and code to work with Azure Machine Learning
• Use automated machine learning to train a machine learning model
• Use Azure Machine Learning designer to train a model
• Run code-based experiments in an Azure Machine Learning workspace
• Create and use datastores and datasets
• Create and use environments and compute targets

TARGET AUDIENCE

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.

CONTENT

• Machine Learning
• Machine Learning Classification Models
• Machine Learning Clustering Models
• Project Jupyter & Notebooks
• Azure Machine Learning Workspaces
• Azure Data Platform Services
• Azure Storage Accounts
• Storage Strategy
• Azure Data Factory
• Non-relational Data Stores

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 containers.

If you are completely new to data science and machine learning, please complete Microsoft Azure AI Fundamentals (AI-900) first.