This course builds on the previous course: IoT Devices. After we have built and programmed a small self-driving vehicle, now it's time get into more advanced territory and enhance the device's connectivity further. To do so you will study radio frequency (RF) communication, the MAC layer, Mesh Networking as well as distributed algorithms for use with geographic locations. These techniques will be applied to your device in the lab, which is composed of four steps, one in each week of the course. In Week 1, after going over some orientation for the course, you will focus on radio frequency (RF) communication, how it fits in with the larger scope of electromagnetism, how RF signals propagate in physical environments, how RF signals can be used to encode data, and how all this information is useful in constructing resilient and high-bandwidth IoT communication substrates.

This course builds on the first two courses in this series: IoT Devices and IoT Communications. Here you will begin to learn enterprise IoT. Enterprise networks, from first-hop access to backend IoT services are critical because they allow your IoT devices to reach the Internet and achieve their true intelligence. IoT places extreme demands on first-hop access - ultra-dense deployments challenge spectrum allocation, the need to provide strong segmentation yet let devices reach into IoT services such as gateways and databases. During this week you will begin to learn about these challenges, and the underlying protocols and technologies of wired networks that can help you to address them.

This course is the last course in our series of four courses and builds on the previous three courses: IoT Devices, IoT Communications, and IoT Networking. After we have built and programmed a small self-driving vehicle, we then set out to enhance its connectivity and add important security infrastructure. In this course we will now look closer into various remaining types of decentralized network topography. In the lab, we will additionally cover important cloud technologies based on machine-learning. In the first two weeks' lectures, we will cover important components of networks. Metaphorically speaking, when you learn how the human body works, you start by understanding the "organs", the stomach, the liver, and so on. Likewise, we can best understand networks by understanding the individual components that make them up and their function. In this lecture series we will study "devices" such as routers, switches, firewalls, load balancers, and many more. We will learn about how they individually operate, how they are configured, and how they work together to achieve various network-wide properties and goals.