Arm Education have just launched our latest Professional Certificate on edX: Advanced Embedded Systems on Arm. Click the following link to enroll in the course now.
The program consists of two courses:
In this blog, we look at the emerging technology trends that led to the development of the program, and what learners can expect when taking the courses.
In a recent Forrester report commissioned by Arm, close to 90% of business leaders are either planning, executing, or expanding their infrastructure, skills base and product offerings to take advantage of the opportunities in IoT. According to the report, “IoT has evolved beyond a hyped buzzword into an infinitely broad set of commercial technologies transforming the way firms operate by sensing, connecting, and automating the physical world.”
We are already starting to see this. With the advent of ‘always-on’ smart devices enabled by Arm and its technology partners, developers are now able to bring their applications closer to where data is being generated – that is closer to the user. By deploying the connectivity of IoT, and the insights enabled by ML, this data can be processed efficiently to create new and innovative applications.
Yet, many firms are facing challenges in developing these transformational applications– mainly due to the lack of in-house expertise and awareness of the fundamental technologies behind distributed computing. Given Arm’s central role in these technologies, we have a leading role to play in providing the next generation of engineers with the skill sets needed to realize the full potential of IoT, ML, and Edge Computing.
This is why we have created our Advanced Embedded Systems on Arm Professional Certificate. By enrolling in the program, learners gain the know-how to build embedded IoT and ML applications on Arm. With Gartner predicting that by 2025 75% of enterprise-generated data will be created and processed by Edge Computing solutions, skilled professionals in this area are in high demand. This program will provide learners with the essential skills needed to unlock the potential of this exciting new world.
This Program is aimed that learners already familiar with the principles of embedded system design. If you are looking to develop your basic embedded systems skills, then we recommend you start your learning journey by taking our Professional Certificate in Embedded Systems Essentials with Arm: https://www.edx.org/professional-certificate/armeducationx-embedded-systems-essentials.
In part 1 of the program, we will give you an overview of the fundamentals of IoT, but quickly move to practical projects that teach you the essentials of building Arm-based IoT applications.
Our labs teach you how to develop programs to control peripherals and sensors on a microcontroller, and how to transmit this data to mobile and cloud-based applications using Bluetooth and Wi-Fi.
We will also provide you with the social context behind the technology with video case studies that illustrate the global impact of IoT applications.
Part 2 of the program focuses on how to train machine learning models and implement them at the ‘Edge’ using industry relevant Arm-based microcontrollers. We will take you through the basics of AI, ML, and ML at the Edge. We will then introduce you to the concept of datasets and how to train ML algorithms to recognize patterns, before exploring advanced topics 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 ML applications. We will cover use cases such as motion and speech recognition, and image processing, using actual sensor data obtained from the microcontroller.
In the final module, you will be able to apply what you have learned by implementing ML algorithms on a dataset of your choice.
Curious to find out more?
 Source: “Scale Up your IoT Offerings with Ecosystem Expertise: A Forrester Consulting Thought Leadership Paper Commissioned by Arm” Forrester Research, Inc., April 2021: https://www.arm.com/resources/report/forrester-scale-iot