본문 영역으로 바로가기
알림창
MLP 온라인 캠퍼스 회원가입
  • 1. 아래 버튼을 클릭해 Office 365 계정 회원가입 진행
    2. MLP 온라인 캠퍼스 바로가기 버튼을 클릭하여 MLP 온라인 캠퍼스에서 로그인

  • ※회원가입에 필요한 인증코드는 소속학교 선생님을 통해 확인하실 수 있습니다.
비디오이미지
진행중 영어

[IOT⑥]IoT 솔루션을위한 예측 분석

  • 코스/코스구분

    IOT / 수료
  • 기관

    Microsoft
  • 언어/번역

    English/영어
  • 학습 기간

    단기(1~5주)
  • 수강 신청 기간

    2019.11.15 ~ 2030.01.01
  • 강좌 수강 기간

    2019.11.15 ~ 2030.01.01

About This Course

<학습 팁>
해당 강좌는 IoT와 머신러닝, 예측 모델을 위한 데이터 준비, 예측 모델을 위한 피처 엔지니어링, 예측 모델의 훈련과 분석에 대해서 설명합니다.
강좌를 수강 완료 시 IoT 시스템 활용, IoT소프트웨어응용, IoT응용실험 등의 과목에 도움이 됩니다.

This course is part of the Microsoft Professional Program Certificate in IoT.

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

What you'll learn

  • 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

Prerequisites

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

Course Syllabus

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

Course Staff

Chris_Howd.png

Chris Howd

Engineer and Software Developer

Microsoft

Chris is an engineer and software developer who has been working at Microsoft in various roles for the past 15 years. Before coming to Microsoft, Chris worked for the U.S. Department of Defense designing and developing computer controlled instrumentation and robotic systems, and was a self-employed contractor doing engineering research with NASA and select engineering start-ups.

Sheila_Shahpari.png

Sheila Shahpari

CTO, Paritta Group

Paritta Group

Frequently Asked Questions

Who can take this course?

Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

키워드 : IOT, 사물인터넷
수강신청

TOP

MS JumpStart AI 온라인 캠퍼스
궁금한 사항이 있으시면 언제든지 편하게 문의해 주세요.
📌 운영 시간 안내
· 평일: 10:00 ~ 18:00
· 운영 시간 외에는 이메일과 카카오톡으로 문의해 주시면
순차적으로 답변드리겠습니다.
/>