20774A: Perform Cloud Data Science with Azure Machine Learning Training

• Describe the Machine Learning and the ways of using its algorithms and languages.
• Explain the main purpose of the Azure Machine Learning and its key features.
• Explore the use the feature engineering and selection methods on the data sets used with the Azure Machine Learning.
• Find out the best uses of the HDInsight with the Azure Machine Learning
• Explore and use the R server with the Azure Machine Learning and define how to organize and configure the SQL Server to provide the best support for R Services.

• Professionals who want to analyze the data by using the Azure Machine Learning can undergo to this course.
• This course is perfect for the Developers, IT Professionals, and Information Workers who are looking for the Azure Machine Learning based support solutions.

• Strong knowledge of Relational databases
• Understanding of common statistical techniques and knowledge of the best practices used in Data Analysis.
• Basic knowledge of the Microsoft Windows Operating System and its main functionalities.
• Experience of Programming using R and knowledge of the common R packages.

Module 1: Introduction to Machine Learning- This module introduces machine learning and discussed how algorithms and languages are used.

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

Module 2: Introduction to Azure Machine Learning- Describe the purpose of Azure Machine Learning, and list the main features of Azure Machine Learning Studio.

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

Module 3: Managing Datasets- At the end of this module the student will be able to upload and explore various types of data in Azure machine learning.

• 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- This module provides techniques to prepare datasets for use with Azure machine learning.

• Data pre-processing
• Handling incomplete datasets

Module 5: Using Feature Engineering and Selection- This module describes how to explore and use feature engineering and selection techniques on datasets that are to be used with Azure machine learning.

• Using feature engineering
• Using feature selection

Module 6: Building Azure Machine Learning Models- This module describes how to use regression algorithms and neural networks with Azure machine learning.

• 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-This module describes how to use classification and clustering algorithms with Azure machine learning.

• Using classification algorithms
• Clustering techniques
• Selecting algorithms

Module 8: Using R and Python with Azure Machine Learning- This module describes how to use R and Python with azure machine learning and choose when to use a particular language.

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

Module 9: Initializing and Optimizing Machine Learning Models- This module describes how to use hyper-parameters and multiple algorithms and models, and be able to score and evaluate models.

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

Module 10: Using Azure Machine Learning Models- This module explores how to provide end users with Azure machine learning services, and how to share data generated from Azure machine learning models.

• Deploying and publishing models
• Consuming Experiments

Module 11: Using Cognitive Services- This module introduces the cognitive services APIs for text and image processing to create a recommendation application, and describes the use of neural networks with Azure machine learning.

• Cognitive services overview
• Processing language
• Processing images and video
• Recommending products

Module 12: Using Machine Learning with HDInsight- This module describes how use HDInsight with Azure machine learning.

• Introduction to HDInsight
• HDInsight cluster types
• HDInsight and machine learning models

Module 13: Using R Services with Machine Learning- This module describes how to use R and R server with Azure machine learning, and explain how to deploy and configure SQL Server and support R services.

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