Internet of Things (IoT) Courses Online

The Internet of Things (IoT) involves the internet-connected devices we use to perform the processes and services that support our way of life. Another component set to help IoT succeed is cloud computing, which acts as a sort of front end. Cloud computing is an increasingly popular service that offers several advantages to IoT, and is based on the concept of allowing users to perform normal computing tasks using services delivered entirely over the internet.[1][2][3] A worker may need to finish a major project that must be submitted to a manager, but perhaps they encounter problems with memory or space constraints on their computing device. Memory and space constraints can be minimized if an application is instead hosted on the internet. The worker can use a cloud computing service to finish their work because the data is managed remotely by a server. Another example: you have a problem with your mobile device and you need to reformat it or reinstall the operating system. You can use Google Photos to upload your photos to internet-based storage. After the reformat or reinstall, you can then either move the photos back to you device or you can view the photos on your device from the internet when you want.

The internet of everything, and all the connected things on the internet, are here to stay. There is considerable hype in the media – good and bad – that makes it difficult to work out if this connectedness is a good thing or a bad thing. Or, should we be indifferent about the internet of everything? What is clear from media coverage is that the internet of everything has already been associated with global security scares, while for many it is the cool technological must-have.

You may not yet have a smartwatch, an Amazon Echo or a refrigerator that has become hackable. However, as we have seen the explosion of smartphones, video technologies and Pokemon, we are witnessing another technology that is set to become a part of everyday life for everyone.

Welcome to the course Internet of everything. The internet of everything (IoE) is the networked connection of people, process, data and things. As more people, data and things come online, we need to develop skills and technological processes to harness the vast amounts of information being generated by all these connected people and things.

The goal of this course is to introduce you to fundamental concepts and technologies that enable the IoE and help you understand its benefits as well as potential risks. The course presents introductory material and is intended to be easily completed by anyone with a basic appreciation of computer technologies. By completing this course, you will not become an IoE expert, but you will become an informed individual...

Implementing edge and IoT systems from sensors to clouds with communication systems, analytics, and security

About

Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is needed if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of IoT devices.

IoT and Edge Computing for Architects, Second Edition encompasses the entire spectrum of IoT solutions, from IoT sensors to the cloud. It examines modern sensor systems, focusing on their power and functionality. It also looks at communication theory, paying close attention to near-range PAN, including the new Bluetooth® 5.0 specification and mesh networks. Then, the course explores IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, Sigfox, and LoRaWAN. It also explains edge computing, routing and gateways, and their role in fog computing, as well as the messaging protocols of MQTT 5.0 and CoAP.

With the data now in internet form, you'll get an understanding of cloud and fog architectures, including the OpenFog standards. the course wraps up the analytics portion with the application of statistical analysis, complex event processing, and deep learning models. the course then concludes by providing a holistic view of IoT security, cryptography, and shell security in addition to software-defined perimeters and blockchains.

Content

• Understand the role and scope of architecting a successful IoT deployment
• Scan the landscape of IoT technologies, from sensors to the cloud and more
• See the trade-offs in choices of protocols and communications in IoT deployments
• Become familiar with the terminology needed to work in the IoT space
• Broaden your skills in the multiple engineering domains necessary for the IoT architect
• Implement best practices to ensure reliability, scalability, and security in your IoT infrastructure

Features

• Build a complete IoT system that's the best fit for your organization
• Learn about different concepts, tech, and trade-offs in the IoT architectural stack
• Understand the theory and implementation of each element that comprises IoT design

Start your IoT Prototyping with Arduino

About

MQ Telemetry Transport (MQTT) is a lightweight messaging protocol for smart devices that can be used to build exciting, highly scalable Internet of Things (IoT) projects.

this course will get you started with a quick introduction to the concepts of IoT and MQTT and explain how the latter can help you build your own internet-connected prototypes. As you advance, you’ll gain insights into how microcontrollers communicate, and you'll get to grips with the different messaging protocols and techniques involved. Once you are well-versed with the essential concepts, you’ll be able to put what you’ve learned into practice by building three projects from scratch, including an automatic pet food dispenser and a smart e-ink to-do display. You’ll also discover how to present your own prototypes professionally. In addition to this, you'll learn how to use technologies from third-party web service providers, along with other rapid prototyping technologies, such as laser cutting, 3D printing, and PCB production.

By the end of this course, you’ll have gained hands-on experience in using MQTT to build your own IoT prototypes.

Content

• Explore MQTT programming with Arduino
• Discover how to make your prototypes talk to each other
• Send MQTT messages from your smartphone to your prototypes
• Discover how you can make websites interact with your prototypes
• Learn about MQTT servers, libraries, and apps
• Explore tools such as laser cutting and 3D printing in order to build robust prototype cases

Features

• Leverage the power of MQTT to build a pet food dispenser, e-ink to-do list, and a productivity cube
• Learn about technologies like laser cutting, 3D printing, and PCB production for building robust prototypes
• Explore practical uses cases to gain an in-depth understanding of MQTT

Implement popular deep learning techniques to make your IoT applications smarter

About

Artificial Intelligence is growing quickly, which is driven by advancements in neural networks(NN) and deep learning (DL). With an increase in investments in smart cities, smart healthcare, and industrial Internet of Things (IoT), commercialization of IoT will soon be at peak in which massive amounts of data generated by IoT devices need to be processed at scale.

Hands-On Deep Learning for IoT will provide deeper insights into IoT data, which will start by introducing how DL fits into the context of making IoT applications smarter. It then covers how to build deep architectures using TensorFlow, Keras, and Chainer for IoT.

You’ll learn how to train convolutional neural networks(CNN) to develop applications for image-based road faults detection and smart garbage separation, followed by implementing voice-initiated smart light control and home access mechanisms powered by recurrent neural networks(RNN).

You’ll master IoT applications for indoor localization, predictive maintenance, and locating equipment in a large hospital using autoencoders, DeepFi, and LSTM networks. Furthermore, you’ll learn IoT application development for healthcare with IoT security enhanced.

By the end of this course, you will have sufficient knowledge need to use deep learning efficiently to power your IoT-based applications for smarter decision making.

Content

• Get acquainted with different neural network architectures and their suitability in IoT
• Understand how deep learning can improve the predictive power in your IoT solutions
• Capture and process streaming data for predictive maintenance
• Select optimal frameworks for image recognition and indoor localization
• Analyze voice data for speech recognition in IoT applications
• Develop deep learning-based IoT solutions for healthcare
• Enhance security in your IoT solutions
• Visualize analyzed data to uncover insights and perform accurate predictions

Features

• Understand how deep learning facilitates fast and accurate analytics in IoT
• Build intelligent voice and speech recognition apps in TensorFlow and Chainer
• Analyze IoT data for making automated decisions and efficient predictions

Build a strong and efficient IoT infrastructure at industrial and enterprise level by mastering Industrial IoT network

About

We live in an era where advanced automation is used to achieve accurate results. To set up an automation environment, you need to first configure a network that can be accessed anywhere and by any device. this course is a practical guide that helps you discover the technologies and use cases for Industrial Internet of Things (IIOT).

Hands-On Industrial Internet of Things takes you through the implementation of industrial processes and specialized control devices and protocols. You’ll study the process of identifying and connecting to different industrial data sources gathered from different sensors. Furthermore, you’ll be able to connect these sensors to cloud network, such as AWS IoT, Azure IoT, Google IoT, and OEM IoT platforms, and extract data from the cloud to your devices.

As you progress through the chapters, you’ll gain hands-on experience in using open source Node-Red, Kafka, Cassandra, and Python. You will also learn how to develop streaming and batch-based Machine Learning algorithms.

By the end of this course, you will have mastered the features of Industry 4.0 and be able to build stronger, faster, and more reliable IoT infrastructure in your Industry.

Content

• Explore industrial processes, devices, and protocols
• Design and implement the I-IoT network flow
• Gather and transfer industrial data in a secure way
• Get to grips with popular cloud-based platforms
• Understand diagnostic analytics to answer critical workforce questions
• Discover the Edge device and understand Edge and Fog computing
• Implement equipment and process management to achieve business-specific goals

Features

• Gain hands-on experience working with industrial architecture
• Explore the potential of cloud-based Industrial IoT platforms, analytics, and protocols
• Improve business models and transform your workforce with Industry 4.0

The Internet of Things (IoT) is an integrated part of the future internet where physical and virtual things that can interact with objects, animals, or people receive unique identifiers. It also has self-configuring capabilities that are able to transfer data over an internet network without need of interaction.[1] The Internet of Things has been in development for decades, but the concept wasn't named until 1999. The first internet appliance, for example, was a Coke machine at Carnegie Melon University in the early 1980s. The programmers could connect to the machine over the internet and were able to check the status of the machine and determine whether or not there would be a cold drink awaiting them, should they decide to make the trip down to the machine.[1] Nowadays, IoT is applied to many systems that can benefit humans, including machine-to-machine systems, cloud systems, human-to-machine systems, and big data systems. "Big data" is a buzzword used to describe the massive volume of both structured and unstructured data that accumulates across many enterprises today, data the remains difficult to process and manage by traditional database and software techniques.[2] Big data is important and has the potential to help companies make faster and more intelligent decisions while also improving company operations.[3] A simple example of big data in use: retailers can track user web clicks to identify behavioral trends that improve campaigns, pricing, and product stocking.