PDP Url

Predictive Analytics for IoT Solutions

This course is affiliated with and is part of Microsoft Professional Program Certificate in IoT.

Self-Paced

Learning Style

Microsoft

Provider

Intermediate

Difficulty

12 Hours

Course Duration

Course Info

Download PDF

Certificate

See Sample

tab
About Individual Course:
  • Individual course plan gives you access to this course
$99.00
$99.00
/ Each
3 Learners Have Enrolled For This Course
When you subscribe, you get:
Learn Subscription plan gives you access to this course and over 840 other popular courses
On Sale!
Now Only $39.99 Regular Price $44.99
Now Only $39.99 Regular Price $44.99
/ Month
Team
Pricing
  • Buy 5-9 Enrollments And Save 68% ($12.74 monthly.)
  • Buy 10-19 Enrollments And Save 72% ($11.24 monthly.)
  • Buy 20-above Enrollments And Save 78% ($8.99 monthly.)
3 Learners Have Enrolled For This Course

You have already taken demo for this course.

If you want to get access to demo again, feel free to contact our support at (855) 800-8240

This course is affiliated with and is part of Microsoft Professional Program Certificate in IoT.

Course Information

About this course:

This course is affiliated with and is part of Microsoft Professional Program Certificate in IoT.

Do you wish to learn about your IoT data? Do you want to gain a deeper comprehension of this data by starting the usage of machine learning?

This course is just the right stop for you. Through this course, you will be able to have the opportunity of learning through practical demonstration exercises. These exercises will give you a hands-on lab experience in learning about implementing machine learning which will deliver to you an understanding of scenarios which are common in IoT, like predictive maintenance. By completing this course, the students will be capable to incorporate predictive analytics in their work by using their IoT data.

The course is adequately divided in four modules:

  • Machine learning for IoT
  • Techniques of preparing data
  • Modeling for predictive maintenance
  • Modeling for predicting faults in the system

Learning Objectives:

The course has the following learning objectives:

  • Give description of machine learning scenarios and algorithms which are regularly relevant to IoT
  • Describe the method for Predictive Maintenance using the IoT Solutions Accelerator
  • Devise data for machine learning operations and analysis
  • Integrate the feature engineering technique in the analysis procedure
  • Selecting the relevant machine learning algorithms regarding the pertained business scenario
  • Pinpoint target variables relevant to the type of the algorithm of machine learning
  • Prepare, analyse, and incorporate various regression models in the system
  • Assess the effectiveness of regression models
  • Integrate deep learning to a predictive maintenance scenario

Audience:

This course is suitable for and designed for IoT engineers and IoT developers

Requirements:

Before beginning the course, the students should make sure that they fulfill the requirements. These include the understanding of IoT terminologies and business objectives, understanding of modern software development tools, fundamental aspects of Python programming, know-how of fundamental data analytics methods, and general knowledge of machine learning concepts.

Outline

More Information

More Information
BrandMicrosoft
SubjectsBusiness Productivity
Lab AccessNo
TechnologyMicrosoft
Learning StyleSelf-Paced Learning
Learning TypeCourse
DifficultyIntermediate
Course Duration12 Hours
LanguageEnglish

Reviews

Write Your Own Review
Only registered users can write reviews. Please Sign in or create an account

This Subscription Includes:

Information
Virtual instructor Led

Virtual Classroom Courses

Our virtual instructor-led courses give you access to live instructors training you with other live students in a virtual classroom environment.

200+ Virtual Classroom Courses
Information
Self-Paced

Online Self-Paced Courses

Take self-paced online courses at your convenience and own pace, with unlimited access to courses in various emerging technologies.

700+ Self-Paced Courses
Information
College

E-books blogs, case studies, ariticles

As part of informal learning, our platform will recommend E-books, whitepapers, case studies, articles, and videos. This is AI curated content closely aligned with your learning objectives.

E-books blogs, case studies,...
Information
College

College Accredited Courses

QuickStart courses are accredited by several top schools and universities, including Texas A&M and University of Phoenix. You can print out certificates and also apply them towards your degree plan with them.

College Accredited
Information
Dashboard

Full Learning Dashboard & Analytics

Access all your enrolled, completed, course statistics, and community discussions from one centralized and intuitive learning dashboard with built in analytics, course tracking, time spent, and more.

Analytics/Reporting
Information
Social

QuickStart Discussions

Engage with other learners where you can directly chat, ask questions, and socialize with other learners experts and instructors on a course subject.

Community Access Community Access
Information
Labs

Virtual Labs

Videos and lectures only go so far. Get real world, hands-on practice with virtual labs (not available for all courses).

Virtual Labs Virtual Labs
Information
Live Instructor Support

Live Instructor Mentoring & Support

Get your IT problems solved through a community of mentors, experts and peers. Get live help from experts to answer questions on course material or guidance on a project.

Mentoring & Discussions Mentoring & Discussions
Information
Dashboard

Career Paths

Start a learning pathway towards understanding and mastering your career. With QuickStart career paths, you can fully understanding and being the best in your field.

Learning Paths Learning Paths
Information
Dashboard

Informal Learning

Access to AI curated content from various content publishers which can help in self-directed learning.

Informal Learning Informal Learning
click here