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

This track has a collection of demonstrations, presentations, and interactive labs designed to prepare you for the Microsoft DP-100 exam.

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3 Lectures
3 Labs
Advanced
9h 15m
Certification Prep
Define and Prepare the Development Environment
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Lecture
Coming Soon!

The student will learn how Azure services can support the data science process. They’ll explore common architectures, learn to assess business goals and constraints for determining the correct environment, and setup the relevant development environments to support data science deployments in Azure.

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Performing Feature Engineering
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Lecture
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The student will learn how develop effective and reusable features ready for modeling. Using manual techniques and then automated techniques, the data scientist will be able to handle core data types using SciKit-Learn and Microsoft Python libraries like MMLSpark and Azure Machine Learning Data Prep...

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Developing Models
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Lecture
Coming Soon!

The student will learn how develop robust models. Starting from selecting the right metric to meet business goals, through to building tuned models, and then evaluating the models produced for fitness.

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Real Time Lab
Jan 20 2020
Skill Me Up
Pausable for 72 hours
5h

In this hands-on lab, you will step through 10 exercises where you will use Azure Machine Learning to accomplish several tasks that are essential to the DP 100 Designing and Implementing a Data Science Solution on Azure exam.You will learn how to Create and Deploy a Training Pipeline, Run Experimen...

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Real Time Lab
Oct 5 2019
Skill Me Up
3h 15m

In this hands-on lab, you will use Azure Databricks in combination with Azure Machine Learning service to build, train and deploy desired models. You will learn how to train a forecasting model against time-series data, without any code, by using automated machine learning, and how to score data in ...

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Real Time Lab
Oct 8 2019
Skill Me Up
1h

In this lab, you want to see if there are models that perform better than the one you might manually create. You decide to use Azure Machine Learning service’s AutoML and HyperDrive to simultaneously execute a number of different types of classification models, compare the results, and recommend the...

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