Master industrial IoT concepts from project planning to machine learning, with hands-on sensor calibration and big data analytics.
Master industrial IoT concepts from project planning to machine learning, with hands-on sensor calibration and big data analytics.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Developing Industrial Internet of Things Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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Instructors:
English
پښتو, বাংলা, اردو, 3 more
What you'll learn
Learn effective project staffing and execution techniques
Master sensor calibration and measurement validation
Understand file systems and big data storage solutions
Gain practical machine learning algorithm knowledge
Develop skills in big data analytics and preparation
Skills you'll gain
This course includes:
7.7 Hours PreRecorded video
4 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course combines practical project management with advanced IoT concepts. Students learn essential skills in project planning, staffing, and execution while diving deep into technical aspects like sensor calibration, file systems, and machine learning algorithms. The curriculum covers both theoretical foundations and hands-on applications, including product development, big data analytics, and practical machine learning implementations in industrial IoT contexts. Special emphasis is placed on real-world applications and industry-relevant skills.
Project Planning and Staffing
Module 1 · 10 Hours to complete
Sensors and File Systems
Module 2 · 2 Hours to complete
Machine Learning
Module 3 · 2 Hours to complete
Big Data Analytics
Module 4 · 2 Hours to complete
Fee Structure
Instructor
Adjunct Professor
David Sluiter is an Adjunct Professor in the Department of Electrical, Computer, and Energy Engineering at the University of Colorado Boulder, where he has been teaching since the Fall of 2016. He specializes in logic design and has developed courses such as "Developing the Industrial Internet of Things" for the Embedded Systems Engineering Program. With a Bachelor of Science in Electrical and Computer Engineering from Michigan Technological University, Sluiter brings extensive industry experience to his academic role.Before joining CU Boulder, Sluiter worked in various engineering positions, including designing cache controllers and floating-point units for Sperry Univac's mainframes and developing 3D graphics chips for a graphics company. He played a key role in establishing LSI Logic's first office in Colorado and later contributed to Seagate's development of self-encrypting hard drives and solid-state enterprise drives. His expertise spans physical layout design, Verilog/SystemVerilog programming, logic synthesis, and storage protocols such as SATA, SAS, and PCIe/NVMe. Through his courses on Industrial IoT Markets and Security, Modeling and Debugging Embedded Systems, and Project Planning with Machine Learning, David Sluiter aims to prepare students for the evolving landscape of embedded systems and IoT technology.
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Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.