| Machine Learning for Data Science and Analytics  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.
Introduction to Cybersecurity  This self-paced four-week University of Washington course is designed to help learners "gain an overview of the cybersecurity landscape as well as national (USA) and international perspectives on the field." The course is free to take and requires on average two to five hours a week of effort. | 
Here is one more journal article on the topic of cyberbiosecurity, this time discussing related vulnerabilities and the need for a resilient infrastructure to limit them. Schabacker et al. of the Argonne National Laboratory present a base "assessment framework for cyberbiosecurity, accounting for both security and resilience factors in the physical and cyber domains." They first discuss the differences between "emerging" and "converging" technologies and how they contribute to vulnerabilities, and then they lead into risk mitigation strategies. The authors also provide clear definitions of associated terminology for common understanding, including the topics of dependency and interdependency. Then they discuss the basic framework, keeping vulnerabilities in mind. They close with a roadmap for a common vulnerability assessment framework, encouraging the application of "lessons learned from parallel efforts in related fields," and reflection on "the complex multidisciplinary cyberbiosecurity environment."
