Open-source software has been a topic of discussion for decades, both as a model of software development and distribution and as a potential for what could be done with it. But the concept of open-source hardware, particularly in the field of science, has been more challenging to address. In this brief perspective article by University of Tübingen's André Maia Chagas, he discusses the benefits of open science hardware to address the growing concern of "haves and have nots" in the scientific research community. Citing high prices, the overall closed-source nature of equipment, businesses that can close without warning, and poor customer support, Chagas attempts to demonstrate that advances in modern design—such as the smartphone—and organizational efforts to implement and promote open hardware philosophies provide opportunity for more people to engage in scientific endeavors. He concludes we "need to reassess our relationship to knowledge and technology, how it determines our role in society, and how we want to spend grant money entrusted to us by the people," and by focusing on making hardware more open and accessible, we'll shrink the divide and improve scientific research as a result.
This is a Columbia University-created course that is released on the edX platform. The self-paced five-week course is designed to help learners "develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics." The course is free to take.