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Course Skill Level:

Foundational to Intermediate

Course Duration:

3 day/s

  • Course Delivery Format:

    Live, instructor-led.

  • Course Category:

    AI / Machine Learning

  • Course Code:


Who should attend & recommended skills:

Those with basic Linux and IT, MS Azure, & ML skills seeking to leverage Azure cloud technologies to implement ML, cognitive services, & AI solutions

Who should attend & recommended skills

  • This course is geared for those with basic Linux and computing skills who wish to start practical machine learning with Azure and to implement machine learning, cognitive services, and artificial intelligence solutions by leveraging Azure cloud technologies.
  • Foundation-level Linux and azure skills for Intermediate skilled team members. This is not a basic class.
  • IT Skills: Basic to Intermediate (1-5 years’ experience)
  • Microsoft Azure: Basic to Intermediate (1-5 years’ experience)
  • Machine Learning: Basic to Intermediate (1-5 years’ experience)
  • Linux: Basic (1-2 years’ experience), including familiarity with command-line options such as ls, cd, cp, and su

About this course

Implementing Machine learning (ML) and Artificial Intelligence (AI) in the cloud had not been possible earlier due to the lack of processing power and storage. However, Azure has created ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML projects in the cloud in a cost-effective way. The course begins by covering the benefits of ML and AI in the cloud. You will then explore Microsofts Team Data Science Process to establish a repeatable process for successful AI development and implementation. You will also gain an understanding of AI technologies available in Azure and the Cognitive Services APIs to integrate them into bot applications. This course lets you explore prebuilt templates with Azure Machine Learning Studio and build a model using canned algorithms that can be deployed as web services. The course then takes you through a preconfigured series of virtual machines in Azure targeted at AI development scenarios. You will get to grips with the ML Server and its capabilities in SQL and HDInsight. In the concluding lessons, you will integrate patterns with other non-AI services in Azure.

Skills acquired & topics covered

  • Working in a hands-on learning environment, led by our Machine Learning with Azure expert instructor, students will learn about and explore:
  • Advanced concepts in Azure ML and the Cortana Intelligence Suite architecture
  • ML Server using SQL Server and HDInsight capabilities
  • Implementing various tools in Azure to build and deploy machine learning models
  • The benefits of leveraging the cloud for ML and AI
  • Using Cognitive Services APIs to build intelligent bots
  • Building a model using canned algorithms from Microsoft and deploy it as a web service
  • Deploying virtual machines in AI development scenarios
  • Applying R, Python, SQL Server, and Spark in Azure
  • Building and deploying deep learning solutions with CNTK, MMLSpark, and TensorFlow
  • Implementing model retraining in IoT, Streaming, and Blockchain solutions
  • Best practices for integrating ML and AI functions with ADLA and logic apps

Course breakdown / modules

  • The importance of artificial intelligence
  • The emergence of the cloud
  • The Microsoft cloud Azure

  • TDSP stages
  • Tools for TDSP

  • Cognitive Services for Vision APIs
  • The Computer Vision API
  • Face API
  • Cognitive Services for Language APIs
  • Cognitive Services for Speech APIs
  • Cognitive Services for Knowledge APIs
  • Cognitive Services for Search APIs

  • What is a bot?
  • Creating a bot with Bot Service

  • Deploying an Azure AI Gallery template
  • Building an experiment
  • Deploying a model as a web service

  • Different scalable compute options in Azure
  • Introduction to DSVMs
  • DLVM
  • Batch AI service
  • ACI
  • AKS

  • What is Microsoft ML Server?
  • Machine learning with Python