Course Code: 5427

55162 Creating and Deploying in Minutes No-Code Predictive Analytics Using Azure Machine Learning

Class Dates:
Length:
2 Days
Cost:
$995
Class Time:
Technology:
Delivery:

Overview

  • Course Overview
  • This course is designed to introduce the participant to the exciting world of predictive analytics built using drag-and-drop with Microsoft Azure Machine Learning Studio, all without coding from your desktop, using your browser.
  • Audience
  • The course is targeted towards business analysts, business intelligence developers, and managers interesting in exploring the world of predictive analytics for use as a competitive tool.

Prerequisites

  • Before attending this course, students must have:
    • Working knowledge of their own business data.
  • Recommended Courses:

Course Details

  • Module 1: Course Overview
  • Introduction
  • Course Materials
  • Facilities
  • Prerequisites
  • What We'll Be Discussing
  • Lab : Course Overview
  • Module 2: What is Machine Learning?
  • Introdcution
  • One Methodology
  • Supervised vs. Unsupervised Methods
  • Analytics Spectrum
  • Development Methodology with Azure Machine Learning Studio
  • Be Very Vigilant
  • Lab : What is Machine Learning?
  • Module 3: Introduction to Azure Machine Learning Studio
  • Experiments
  • Web Services
  • Notebooks
  • Datasheets
  • Trained Models
  • Settings
  • Walkthrough Exercise and Group Discussions
  • Lab : Introduction to Azure Machine Learning Studio
  • Module 4: Data Preparation
  • Tools for Cleaning
  • Text Files vs. Binary Files
  • Structures of Data
  • Steps for Data Cleaning
  • Common Cleaning Tasks
  • Feature Selection
  • Feature Engineering
  • Group Discussion
  • Lab : Data Preparation
  • Module 5: Machine Learning Algorithms
  • Regression
  • Classification
  • Clustering
  • Anomaly Detection
  • Azure Machine Learning Cheat Sheet
  • Visualizations
  • Group Discussion and Exercises
  • Lab : Machine Learning Algorithms
  • Module 6: Building Models - Exercises
  • Group Discussion 1: Data Acquisition
  • Group Discussion 2: Data Preparation
  • Group Discussion 3: Feature Selection
  • Group Discussion 4: Train Data
  • Group Discussion 5: Cross Validation and Comparing Regressions
  • Group Discussion 6: Results
  • Group Discussion: Evaluate the Solutions - Learn from Examples
  • Lab : Building Models - Exercises
  • Module 7: Visualizing Analytical Models with Power BI
  • What is Power BI?
  • Creating a Power BI Account
  • Deploying to Power BI
  • Visualizations
  • Lab : Visualizing Analytical Models with Power BI