Materials are a lot. Lectures are very compact. We need to invest a lot of time to be able to grasp the whole concept. Lecturers are very good. There are 3 lecturers during my time and they are competent in their specific area.

Lectures are insufficient in time but tutorials are good.

Fun intro to machine learning, information retrieval and approximate string search. Projects are self-driven so it's up to you to set how far you're willing to delve into them. Quality projects are rewarded with good marks and reviews.

Knowledge Technologies = Information Retrieval + Intro to Machine Learning. So you never find a subject with this name. The subject is fascinating and will be stepping stone if you want to be a data scientist or Machine Learning designer. Two lectures teach the subject, one who specialised to the ML was not good at teaching. Projects and mid-semester are Ok (the only thing most of the cases, there is no strict explanation what you should do in the projects) but final exam is tough to complete in 2 hours. So be prepared very well: learn every technique with calculation and you should able to analyze the result. Overall, very challenging and rewarding subject.