I've just checked the time table of this course and got to know it has changed. Why do we have two lectures and one exercise in this week? Since I'm not from the area of computer science, it is really hard to keep up this pace. I think we already had several lectures of over 2hr, more than 1.5hr.
Indeed, the lecture was filed under the wrong date. Thanks for spotting the error. Some videos are longer because I give more explanations than I would normally do in classes. The same material has been taught in 90min lectures in the past, and I could also shorten my talking accordingly, but I find that saying a few more things is useful on video, where I do not have feedback from the audience. I appreciate that the course is not easy for students without prior exposition to computer science. It's not so much because of the required prior knowledge (which are just some very basic ideas from algorithmic complexity), but because of the typical computer science skill set that we built on. Already at BSc level, computer scientists are routinely dealing with abstract concepts, technical specifications, and the underlying mathematical models. For students from areas where other skills have been developed at BSc level, this course will implicitly be not just about Knowledge Graphs, but also about some "computer science thinking" that is new to them, which is of course an extra challenge. Studying in an interdisciplinary programme like TU Dresden's "Computional Modeling and Simulation" is always an extra challenge -- but if you live up to it, the reward is a unique multi-disciplinary perspective that few experts have.
I've just checked the time table of this course and got to know it has changed. Why do we have two lectures and one exercise in this week? Since I'm not from the area of computer science, it is really hard to keep up this pace. I think we already had several lectures of over 2hr, more than 1.5hr.
Indeed, the lecture was filed under the wrong date. Thanks for spotting the error. Some videos are longer because I give more explanations than I would normally do in classes. The same material has been taught in 90min lectures in the past, and I could also shorten my talking accordingly, but I find that saying a few more things is useful on video, where I do not have feedback from the audience.
I appreciate that the course is not easy for students without prior exposition to computer science. It's not so much because of the required prior knowledge (which are just some very basic ideas from algorithmic complexity), but because of the typical computer science skill set that we built on. Already at BSc level, computer scientists are routinely dealing with abstract concepts, technical specifications, and the underlying mathematical models. For students from areas where other skills have been developed at BSc level, this course will implicitly be not just about Knowledge Graphs, but also about some "computer science thinking" that is new to them, which is of course an extra challenge. Studying in an interdisciplinary programme like TU Dresden's "Computional Modeling and Simulation" is always an extra challenge -- but if you live up to it, the reward is a unique multi-disciplinary perspective that few experts have.
@@knowledge-basedsystemstudr9413 Thank you for kind reply
anyone else having a hard time keeping their eyes open while watching?
It is dry material but I found the 3 views of property graphs to be very interesting.