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MS-20774 - Perform Cloud Data Science with Azure Machine Learning

The main purpose of the course is to give students the ability to analyze and present data by using Azure Machine Learning, and to provide an introduction to the use of machine learning with big data tools such as HDInsight and R Services.

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Prerequisites


In addition to their professional experience, students who attend this course should have:
  • Programming experience using R, and familiarity with common R packages
  • Knowledge of common statistical methods and data analysis best practices.
  • Basic knowledge of the Microsoft Windows operating system and its core functionality.
  • Working knowledge of relational databases.

Detailed Class Syllabus


Module 1: Introduction to Machine Learning


What is machine learning?
Introduction to machine learning algorithms
Introduction to machine learning languages

Module 2: Introduction to Azure Machine Learning


Azure machine learning overview
Introduction to Azure machine learning studio
Developing and hosting Azure machine learning applications

Module 3: Managing Datasets


Categorizing your data
Importing data to Azure machine learning
Exploring and transforming data in Azure machine learning

Module 4: Preparing Data for use with Azure Machine Learning


Data pre-processing
Handling incomplete datasets

Module 5: Using Feature Engineering and Selection


Using feature engineering
Using feature selection

Module 6: Building Azure Machine Learning Models


Azure machine learning workflows
Scoring and evaluating models
Using regression algorithms
Using neural networks

Module 7: Using Classification and Clustering with Azure machine learning models


Using classification algorithms
Clustering techniques
Selecting algorithms

Module 8: Using R and Python with Azure Machine Learning


Using R
Using Python
Incorporating R and Python into Machine Learning experiments

Module 9: Initializing and Optimizing Machine Learning Models


Using hyper-parameters
Using multiple algorithms and models
Scoring and evaluating Models

Module 10: Using Azure Machine Learning Models


Deploying and publishing models
Consuming Experiments

Module 11: Using Cognitive Services


Cognitive services overview
Processing language
Processing images and video
Recommending products

Module 12: Using Machine Learning with HDInsight


Introduction to HDInsight
HDInsight cluster types
HDInsight and machine learning models

Module 13: Using R Services with Machine Learning


R and R server overview
Using R server with machine learning
Using R with SQL Server