Advanced Embedded Systems on Arm

Overview

Syllabus

Courses

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  7 weeks, 3-6 hours a week, 3-6 hours a week

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  Arm technology powered the smartphone revolution, and now it’s helping power the Internet of Things (IoT). This online course will provide beginners with an accelerated path to gain the knowledge necessary to thrive in a world transformed by innovations in IoT.

  You can purchase the bill of materials required for the course directly from our technology partner, STMicroelectronics: https://www.st.com/content/st_com/en/campaigns/educationalplatforms/iot-arm-edx-edu.html

  Instructor Update: We've identified an issue with the Google IoT Cloud service used in Modules 5 and 6 of the course. We are working to implement a solution to fix this issue and will update learners on our progress.

  You’ll start your learning journey in this course by understanding the fundamentals of IoT, but quickly move to practical projects that will teach you the essentials of building Arm-based IoT applications.

  Given that mobile computing platforms are where IoT often happens, we’ll also give you a basic understanding of Android application design, so you can integrate your mobile device into your IoT applications.

  IoT applications have the potential to change the lives of billions around the world. This is why we’ll also provide you with the social context behind the technology. The course includes videos that illustrate the global impact of IoT applications – especially in emerging economies such as Africa. From ‘smart farming’, to solar panels and ‘blood drones’ - each case study contextualises IoT in real ‘first mile’ and ‘last mile’ applications, to help you understand the transformative impact of this technology in the real world.

  Over the 6 modules, you will gain a key overview of:

  • Internet of Things (IoT) fundamentals

  • IoT and embedded system architectures

  • Embedded application programming

  • Connectivity and networking technologies such as Bluetooth Low Energy (BLE), LoRaWAN, ZigBee, and the IEEE 802.1 protocols

  • Cloud computing

  While not a requirement for this course, we recommend that learners who would like to improve their embedded systems skills (one of the essential technologies behind IoT implementations), also take our Embedded Systems Essentials on Arm edX program.

  The Internet of Things is one of the fundamental building blocks of the next wave of computing. Forge your own career path in this connected world by enrolling in our course today!

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  6 weeks, 3-6 hours a week, 3-6 hours a week

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  The age of machine learning has arrived! Arm technology is powering a new generation of connected devices with sophisticated sensors that can collect a vast range of environmental, spatial and audio/visual data. Typically this data is processed in the cloud using advanced machine learning tools that are enabling new applications reshaping the way we work, travel, live and play.

  To improve efficiency and performance, developers are now looking to analyse this data directly on the source device – usually a microcontroller (we call this ‘the Edge’). But with this approach comes the challenge of implementing machine learning on devices that have constrained computing resources.

  This is where our course can help!

  By enrolling in Machine Learning at th e Edge on Arm: A Practical Introduction you’ll learn how to train machine learning models and implement them on industry relevant Arm-based microcontrollers.

  We’ll start your learning journey by taking you through the basics of artificial intelligence , machine learning and machine learning at the edge , and illustrate why businesses now need this technology to be available on connected devices. We’ll then introduce you to the concept of datasets and how to train algorithms using tools like Anaconda and Python. We'll then go on to explore advanced topics in machine learning such as artificial neural networks and computer vision.

  Along the way, our practical lab exercises will show you how you can address real-world design problems in deploying machine learning applications, such as speech and pattern recognition, as well as image processing, using actual sensor data obtained from the microcontroller. We'll also introduce you to the open source TensorFlow Python library, which is useful in the training and inference of deep neural networks.

  In the final module you’ll be able to apply what you’ve learned by implementing machine learning algorithms on a dataset of your choice.

  The ST DISCO-L475E board used in this course can be purchased directly from our technology partner STMicroelectronics: https://www.st.com/content/st_com/en/campaigns/educationalplatforms/iot-arm-edx-edu.html

  Through our vast ecosystem, Arm already powers a wide range of devices and applications that rely on machine learning at the edge. Be a part of this vibrant community of developers and start your machine learning journey by enrolling in our course today!

Taught by

Mark Allen, Michele Magno and Tom Spink