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Data Science on Azure

Build and deploy data science and machine-learning solutions using Azure services, Databricks, and Power BI.

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Audience: Developers / Architects

Duration: 4 days

Format: Lectures and hands-on labs (50% lecture, 50% lab)

Overview

Data Science spans statistics, visualization, exploration, and machine learning. Since Microsoft Azure is the second-largest cloud computing provider, knowledge of its Data Science capabilities is essential for building best-of-breed solutions. Azure's strength is in its usability and integration with the Microsoft stack. This course introduces ML with Python and R and dives into Azure's specific tools for data science.

Objective

Build and deploy data science and machine-learning solutions using Azure services, Databricks, and Power BI.

What You Will Learn

  • R and Python data science fundamentals
  • Azure Machine Learning and Data Science IDE
  • Spark and Databricks runtime
  • Machine Learning workflows
  • Streaming analytics on Azure

Course Details

Audience: Developers / Architects

Duration: 4 days

Format: Lectures and hands-on labs (50% lecture, 50% lab)

Prerequisites:
  • Interest in Machine Learning (overview included)
  • Familiarity with Python or R is a plus

Setup: A modern laptop · Unrestricted Internet · Chrome browser · SSH client

Detailed Outline

  • Machine Learning Concepts
  • Machine Learning Approaches
  • Supervised Learning
  • Unsupervised Learning
  • Machine Learning Life Cycle
  • Machine Learning Languages and Platforms
  • Installing RStudio, Installing Packages
  • R Data Structure
  • Vector, Factor, Lists, Data Frames
  • R for Statistical Analysis
  • R for Machine Learning
  • R for Visualization
  • Python IDE
  • Install Packages
  • Python for Statistical Summary
  • Statistical Distribution
  • Python for Visualization
  • Python for Machine Learning
  • Power BI
  • Setting Up R in Power BI
  • Writing R Code in Power BI
  • R Features in Power BI
  • Slice and Dice
  • Edit R Code in RStudio
  • Predictive Analysis in Power Query with R
  • Neural Networks
  • Decision Trees
  • Automated Machine Learning Inside Power Query
  • Databricks Environment
  • Machine Learning on Databricks
  • Linear Regression
  • Logistic Regression
  • SVN
  • Decision Trees, Random Forests
  • R in Azure Data Lake
  • Azure Data Lake Environment
  • Running R Scripts in U-SQL
  • Azure Machine Learning Studio
  • Event Hub
  • Application
  • Azure Stream Analytics
  • Azure Machine Learning (ML) Workbench
  • Deep Learning Tools with Cognitive Toolkit

Ready to Get Started?

Contact us to learn more about this course and schedule your training.