Besides the committee that every member is part of, and the case that everyone has to do for a company, there will also be a theme course. Setting this up is being realized by the Education committee. At this point we are ready to tell you more about its theme and content.
As the title says, the theme is ‘machine learning’: the science of getting computers to act without being explicitly programmed. Some modern examples are self-driving cars, practical speech recognition and effective web search.
In this course, we will learn about a variety of topics, among others: Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks), unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning) and best practices ( bias/variance theory, innovation process in machine learning and AI).
More importantly, we will gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. We will practice how to apply the learning algorithms to build smart robots, text understanding, computer vision, database mining and other applications. We will do this via practical lab sessions.
The course is scheduled over a semester, starting in February.