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Predictive Analytics for IoT Solutions

Learn how to apply machine learning to your IoT data and gain a valuable advantage over your business competition. This course provides hands-on experience developing predictive maintenance and other ML solutions for IoT scenarios.

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微软
edX
  • 完成时间大约为 4
  • 中级
  • 英语
注:因开课平台的各种因素变化,以上开课日期仅供参考

你将学到什么

Describe machine learning scenarios and algorithms commonly pertinent to IoT

Explain how to use the IoT solution Accelerator for Predictive Maintenance

Prepare data for machine learning operations and analysis 

Apply feature engineering within the analysis process

Choose the appropriate machine learning algorithms for given business scenarios 

Identify target variables based on the type of machine learning algorithm

Train, evaluate, and apply various regression models

Evaluate the effectiveness of regression models

Apply deep learning to a predictive maintenance scenario

课程概况

Are you ready to start using machine learning to develop a deeper understanding of your IoT data? 

This course uses hands-on lab activities to guide students through a series of machine learning implementations that are common for IoT scenarios, such as predictive maintenance. After completing this course, students will be able to implement predictive analytics using their IoT data.

The course is divided into four modules that cover the following topic areas:

Machine learning for IoT
Data preparation techniques
Predictive maintenance modeling
Fault prediction modeling

课程大纲

This course is completely lab-based. There are no lectures or required reading sections. All of the learning content that you will need is embedded directly into the labs, right where and when you need it. Introductions to tools and technologies, references to additional content, video demonstrations, and code explanations are all built into the labs. Some assessment questions will be presented during the labs. These questions will help you to prepare for the final assessment.The course includes four modules, each of which contains two or more lab activities. The lab outline is provided below.Module 1: Introduction to Machine Learning for IoT

Lab 1: Examining Machine Learning for IoT
Lab 2: Getting Started with Azure Machine Learning
Lab 3: Exploring Code-First Machine Learning with Python

Module 2: Data Preparation for Predictive Maintenance Modeling

Lab 1: Exploring IoT Data with Python
Lab 2: Cleaning and Standardizing IoT Data
Lab 3: Applying Advanced Data Exploration Techniques

Module 3: Feature Engineering for Predictive Maintenance Modeling

Lab 1: Exploring Feature Engineering
Lab 2: Applying Feature Selection Techniques

Module 4: Fault Prediction

Lab 1: Training a Predictive Model
Lab 2: Analyzing Model Performance

预备知识

Before starting this course, students should understand the following:

IoT terminology and business goals
How to use modern software development tools
Basic principles of Python programming
Basic data analytics techniques
General machine learning concepts

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