Developing Industrial Internet of Things

In Industrial IoT Markets and Security, students will learn about markets (Transportation, Agriculture and more), platforms (IBM Watson Cloud services for example), software and services, networking basics, wireless communications protocols and a thorough introduction to computer security. Developing tomorrow's industrial infrastructure is a significant challenge. This course goes beyond the hype of consumer IoT to emphasize broader application areas such as Advanced Manufacturing and Building Automation. The Industrial Internet of Things (IIoT), is also known as Industry 4.0. Cisco’s CEO stated: “IoT overall is a $19 Trillion market. IIoT is a significant subset including digital oilfield, advanced manufacturing, power grid automation, and smart cities”. This is part 1 of the specialization. The primary objective of this specialization is to closely examine emerging markets, technology trends, applications and skills required by engineering students, or working engineers, exploring career opportunities in the IIoT space. The structure of the course is intentionally wide and shallow: We will cover many topics, but will not go extremely deep into any one topic area, thereby providing a broad overview of the immense landscape of IIoT. There is one exception: We will study security in some depth as this is the most important topic for all "Internet of Things" product development. In this course students will learn : * What Industry 4.0 is and what factors have enabled the IIoT. * Key skills to develop to be employed in the IIoT space. * What platforms are, and also market information on Software and Services. * What the top application areas are (examples include Manufacturing and Oil & Gas). * What the top operating systems are that are used in IIoT deployments. * About networking and wireless communication protocols used in IIoT deployments. * About computer security; encryption techniques and secure methods for insuring data integrity and authentication. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Electrical Engineering (MS-EE) degree offered on the Coursera platform. The degree offers targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Electrical Engineering: https://www.coursera.org/degrees/msee-boulder

Products don't design and build themselves. In this course, students learn how to staff, plan and execute a project to build a product. We explore sensors, which produce tremendous volumes of data, and then storage devices and file systems for storing big data. Finally, we study machine learning and big data analytics. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Electrical Engineering (MS-EE) degree offered on the Coursera platform. The degree offers targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Electrical Engineering: https://www.coursera.org/degrees/msee-boulder