Seminar: Interactive Visual Data Analysis (BSc, MSc)

Topic Focus:

Interactive visual data analysis focuses on the combination of the strengths of humans and computers to address complex data analysis challenges. Solutions typically include interactive visual interfaces, enabling users to participate actively in the data science and machine learning process (human-in-the-loop). Course Mechanics: In groups, students will study a seminar topic of interest, compile a structured list of references, prepare a compelling fact sheet about the topic, and present the topic in class. In parallel, students will receive mentoring by the supervisor, give constructive feedback on other student's work, and participate actively in the presentation rounds.

Learning Goal:

At the end of the course, students:

• have gained a deeper and broader understanding and knowledge of interactive visual data analysis as a whole
• will be able to identify and discuss research problems as well as identify relevant related work
• will be able to write a fact sheet about a specific topic in data analysis research, present the topic to a student audience, and discuss ideas on the topic.
• will have learned to accept and give feedback on students’ seminar contributions

Assessment:

• Fact sheet (25%)
• References list (10%)
• Quality of feedback on other students' fact sheets (15%)
• Presentation slides (15%)
• Presentation of the topic (15%)
• Discussion, Q+A (20%)