Powering your Home Projects with Raspberry Pi Specialization

In this course you will use a Raspberry Pi 4 to build a complete network-connected project with sensors and motors and access it from your smartphone. We'll explore all the parts which make this work, so you can use this experience as a foundation for your own projects. We'll use the Raspberry Pi as an "embedded system" (as opposed to a desktop computer) so you're ready to build a Raspberry Pi into your projects as the brains that make it all work. Want to build your own Internet of Things (IoT) device? Home automation? Robotics? This is the class to learn how it all works, to get you building on your own. No experience in embedded systems, programming, or electronics is assumed, and optional bonus sections are provided for those who want a fast start in Python programming, Linux essentials, and basic electronics. The course is divided into four modules to explore each focus area with demontrations and extras along the way: 1) installing and configuring a Raspberry Pi, 2) accessing the Raspberry Pi over the network, 3) programmatically controlling external sensors and motors, and 4) accessing the embedded device through a web interface. After these four modules you'll get started building your own projects right away, and the three follow-on courses in this Coursera specialization dive into each area to really boost your skills and the complexity of your projects. I hope you enjoy all the courses and I hope you take your builds to the next level.

Course two of this specialization is all about hardware physical layer and communication between elements of your project, how to troubleshoot high-speed signals when they don't work, and how to design your projects so they do work.

We start with a review of common signal protocols available . Then, to build a deep and intuitive understanding of how circuits send and receive these signals, Module 2 explores the physics of high-frequency signals in an easy-to-follow way. Module 3 flips your thinking from the time-domain to the frequency-domain to examine the frequency components of signals and understand how unintended filtering in your circuits distorts your digital waveforms. These are "signal integrity" concepts, distilled to what you need for your Raspberry Pi projects. Now, with our knowledge of signals, Module 4 develops five rules of thumb for designing your circuits so that your high-speed signals work the first time. These five rules of thumb, combined with the experience from earlier modules, help you estimate spectral bandwidth of signals, rise time, and gain insights whether you're troubleshooting a broken design or designing something new.

This course on integrating sensors with your Raspberry Pi is course 3 of a Coursera Specialization and can be taken separately or as part of the specialization. Although some material and explanations from the prior two courses are used, this course largely assumes no prior experience with sensors or data processing other than ideas about your own projects and an interest in building projects with sensors.

This course focuses on core concepts and techniques in designing and integrating any sensor, rather than overly specific examples to copy. This method allows you to use these concepts in your projects to build highly customized sensors for your applications. Some of the ideas covered include calibrating sensors and the trade-offs between different mathematical methods of storing and applying calibration curves to your sensors. We also discuss accuracy, precision, and how to understand uncertainty in your measurements. We study methods of interfacing analog sensors with your Raspberry Pi (or other platform) with amplifiers and the theory and technique involved in reducing noise with spectral filters. Lastly, we borrow from the fields of data science, statistics, and digital signal processing, to post-process our data in Python.