The course will give students an overview of selected topics in advanced machine learning that are currently subjects of active research. The course concludes with a final project.

In this seminar, recent papers of the pattern recognition and machine learning literature are presented and discussed. Possible topics cover statistical models in computer vision, graphical models and machine learning.

No description available.

Contemporary web development utilizes a technology stack that spans from back-ends to front-ends, and includes virtual server environments, document databases, back-end and front-end programming, and UI/UX design. The depth of this stack fosters separation of concernand reuse, but also amounts to a steep learning curve.

This is an interdisciplinary course at the intersection of computer science, peace and security, global health, and climate science. Students will implement practical projects that involve the application of their skills on public data to address global challenges. In addition, students will critically engage with the ethical, social, and political implications of using AI for global challenges.

Visual Analytics supports the design of human-in-the-loop interfaces that enable human-machine collaboration. In this course, will go through the fundamentals of designing interactive visualizations, later applying them to explain and interact with machine leaning models.