Using Docker Containers in Teaching of Advanced Data Analytics Methods

In this paper we consider an important problem in teaching of advanced theory is that you need access to complicated software. In many cases in order to allow students to participate in more challenging classes, like Bayesian data analysis, or advanced FPGA programming you encounter an issue that setting up the relevant software on their machines consumes significant part of the course, and you need to troubleshoot issues that are irrelevant to the actual topic. We present a solution from our own experience that is using container software i.e. Docker and we show how it significantly improved our work when teaching data analytics and Bayesian methods in general.