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Microsoft

Course 40502-G: Microsoft Cloud Workshop: Big Data & Visualization

  • Duration: 1 days
  • Job Role: Data Engineer

Course 40502-G: Microsoft Cloud Workshop: Big Data & Visualization

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In this workshop, you will deploy a web app using Machine Learning (ML) to predict travel delays given flight delay data and weather conditions. Plan a bulk data import operation, followed by preparation, such as cleaning and manipulating the data for testing, and training your Machine Learning model.

Audience Profile

This workshop is intended for Cloud Architects and IT professionals who have architectural expertise of infrastructure and solutions design in cloud technologies and want to learn more about Azure and Azure services as described in the “Summary” and “Skills gained” areas. Those attending this workshop should also be experienced in other non-Microsoft cloud technologies, meet the course prerequisites, and want to cross-train on Azure.

Prerequisites

  • Knowledge of cloud computing.

Course outline

Module 1: Whiteboard Design Session - Big data and visualization
Module Overview

In this module, you will work with a group to design a solution for ingesting and preparing historic flight delay and weather data and creating, training, and deploying a machine learning model that can predict flight delays. At the end of this module, you will have learned how to include a web application that obtains weather forecasts from a 3rd party, collects flight information from end-users, and sends that information to the deployed machine learning model for scoring. Part of the exercise will include providing visualizations of historic flight delays and orchestrating the collection and batch scoring of historic and new flight delay data.

Lessons

Review the customer case study
Design a proof of concept solution
Present the solution

Lab Sessions

Not available for this module

Lab Lessons

Lab lessons not available

After completing this module, students will be able to:

Describe case study.
Design concept solution.
Describe solution.

Module 2: Hands-on Lab - Big data and visualization
Module Overview

This module is designed to provide exposure to many of Microsoft’s transformative line of business applications built using Microsoft big data and advanced analytics. By the end of this module, you will be able to show an end-to-end solution, leveraging many of these technologies but not necessarily doing work in every component possible.

Lessons

Build a Machine Learning Model
Setup Azure Data Factory
Deploy your machine learning model with Azure ML
Develop a data factory pipeline for data movement
Operationalize ML scoring with Azure Databricks and Data Factory
Summarize data using Azure Databricks
Visualizing in Power BI Desktop
Deploy intelligent web app

Lab Sessions

Not available for this module

Lab Lessons

Lab lessons not available

After completing this module, students will be able to:

Build a complete machine learning model in Azure Databricks for predicting if an upcoming flight will experience delays.
Store the trained model in Azure Machine Learning Model Management, then deploy to Docker containers for scalable on-demand predictions.
Use Azure Data Factory (ADF) for data movement and operationalizing ML scoring.
Summarize data with Azure Databricks and Spark SQL.
Visualize batch predictions on a map using Power BI.

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