What is a proof, or in other words: how do you establish the truth? How do you distinguish good, reliable literature from bad, unreliable sources? What are essential elements of a good title, abstract, and introduction for your Master's theses and presentation, so that you can capture the readers' interest? Can you summarize and present numbers in charts and tables in such a way that the data, not the statistical methods and the graphic design, determine what trends you observe? How can you deal with conflicting ethical norms that society imposes on you as a researcher or engineer? These are the main questions addressed in this course.
What is a proof? How can you phrase statements so that they can be proven (if true), and how do you distinguish between misleading evidence and a proof that leaves no room for doubt? The answers depend on the type of research (theoretical or empirical/experimental) and the purpose (for example: discovering facts, convincing colleagues, or enabling automatic verification). In fact, computer science is quite an unusual science: it is sometimes more like mathematics, sometimes more like engineering, and sometimes more like natural or social sciences. Mathematics offers us axioms and theoretical models of computation to work with; natural and social sciences offer us the so-called scientific method. What are the requirements and limitations of the corresponding types of proofs? How do you set up experiments? How do you avoid subtle mistakes that lead to drawing wrong conclusions from a theorem or from the results of experiments?
How do you distinguish good, reliable sources from bad, unreliable sources? We will discuss tell-tale signs of reliable and less reliable writings (literature, reports, web pages), and we will discuss the different types of publications in the academic publication system.
What are essential elements of a good title, abstract, and introduction for your writings and presentations? And how do you describe algorithms and proofs that take many pages to explain (as you may have to do in your graduation project), as opposed to a couple of paragraphs (as in most course work)? We put ourselves in the shoes of the readers and see what they need to get interested and convinced.
How do you apply basic statistics and how do you present numbers in charts and tables in such a way that the data, not the graphic design, determines what trends you observe? We will discuss typical bad (misleading) examples and good (enlightening) examples of the use of statistics and visualization.
How can you deal with conflicting requirements that society imposes on you as a researcher or engineer? You may have heard of the university's code of scientific conduct, with its five basic professional ethical norms: trustworthiness, intellectual honesty, openness, independence, and societal responsibility. But in many cases these norms conflict with each other, and ethical dilemmas arise from uncertainty, safety considerations, time constraints, privacy concerns, business or career interests etc. What do you do then? What principles, what practical considerations and what elements in society may influence the decisions you take as a scientist or engineer in these matters?
The course will have lectures, presentations by students, homework exercises, and discussions in the class room. We will meet twice per week, according to the schedule in OASE. Various assignments during the course determine 50% of the final grade; the final exam determines the remaining 50% of the final grade.
To be announced
To be announced.