Excellent course content overall. However, the lack of practical exercises to actually apply what is covered in the lectures really decreases the course value. I would advise to make this an specialization with hands-on practice, since the range of topics the course includes is just too dense to effectively leave a solid, real-world applicable knowledge in 6 weeks.

The course is at introductory level and not intermediate. There is a good "basic information", but no hands-on exercise. That leaves a lot that actually needs to be learned upon the student. So, in my opinion, the course doesnt even consider the skill building at introductory level from an introductory standpoint.

A comprehensive overview of Spatial Analytics tools and processes which I was looking for. However, the speaker's strong accent and sometimes incorrect use of English made learning difficult. This could be a much better course with an updated, revised presentation and a different speaker.

I really want to believe that the lecturer has an in depth knowledge of the topic but as many others pointed out before: The course is providing no practical content at all and from an international academic researcher with multiple years working experience in native English speaking countries I would expect a clear and understandable communication. This was unfortunately not the case. It was very hard to follow the lectures that are "purely read from the slides". Quizzes became indeed hard because of a certain language barriers. Terminologies of teaching (e.g. "In this course you learned [...]" or "In the past course you studied [...]") are a bit misleading into the perception of an applicable understanding of the concepts. But knowledge does not equal understanding. To have "studied" or "learned" a topic one needs to get lectures that are didactically formulated well and maybe provide hands-on experience with the topic. At least giving a small assignment and trying around with QGIS would have provided some value.

I also agree with others that this course should be updated and rerecorded with a speaker that is more comfortable with spoken English. I'm sure Yonsei University can do this!

Very boring and no hands on content.

Overall good course. Rated as intermediate but more beginner in my opinion. Lots of overlap with what i would expect in an 'vanilla' data science course. If youve taken anything like that expect to hear alot of things you have heard before but does thuroughly extend in to the spatial aspect and application.

I would have perferred a little more emphasis on analysis techniques and deeper applications. I was also suprised by no direct application of for the student at all. all video based no hands on.

Last couple of quizes are also pretty tough, mostly from the fact that they are poorly written and difficult to answer from an infromed perspective.

I learned about different spatial data science techniques, but didn't get a chance to try them out. I wish we spent more time on the spatial data analytics portion of the curriculum, and less on spatial data science architectures.

The course is way overloaded with way too many concepts.It should have clear prerequisites and defined educational background before taking.Some concepts are really vaguely described and pushed on.Can really improve on this.

The course presents a good overview of Data Science techniques applied to Spatial Data topics. It is very compact and exhaustive. Mostly theorethical.

I think a second part of this course should be created with in-depth coverage with practical exercises (e.g setting up a hadoop system with MapReduce, pig, Hive).

This way, students could learn a lot more than by simply watching the videos offered. Further, please provide the well designed slides for download.

The theory was very interesting and you learn a lot about spatial data science, as well as something very basic about the proposed architecture. But it takes a lot of practice, the student wants to test and run the practices on their computer (or why name Open Source software?)

Too boring. No practical exercises. I couldn't finish all lectures because I had no more patience for that. I was thinking I would learn how to use QGIS or any tool for GIS, but absolutely not. The slides have links to youtube videos but we can't download the slides.

Great course which starts with basics, gets descriptive with examples, real life scenarios, usage of software. Definitely recommended.

Practical and hands-on exercises should be included to get a close feel of the subject. Only theoretical knowledge gets monotonous. Some topics were well touched upon however, some external resources like books or other courses related to subject would have been very helpful. The youtube links were helpful though.

This course did not meet my expectations. I was expecting that this course would be heavy on hands-on applications of the software used in each discipline of spatial data science. I did not, so I still have to find my own way to learn these open-source software programs. The course, however, explains the four disciplines extensively. It would have been better if the instructor used real-world applications simultaneously with each methodology described so that we can grasp the principles more quickly and intuitively.

No any practice skills, just common words.

The course was able to provide excellent theoretical foundations for spatial data science and its applications. However, some points required more explanation such as that of the spatial big data management system, as this required and asked for a deeper understanding from the student. Despite this, I still think that the course was able to provide ample instruction for spatial data science. Additionally, the course was substantial enough to incite interest for the student to delve deeper into the field. Lastly, there may be advanced solutions for data science in the present day but the course was right in presenting noble solutions and tools since the trustworthiness of the "classics" are unquestionable.

This course is excellent ! IT touches upon all the different topics related to spatial data science in a very straight to the point way. This is extremely beneficial for the spatial data scientist community. What I liked about this course is that it focused on data issues and concepts that I have always struggled with and never found an answer to in other GIS courses which mostly focus on their area of application. This one is generic and the concepts can literally be translated in any field. I think that hands-on exercises would have made it perfect especially in the fourth topic of spatial big data. I will be willing to take another course by this teacher especially if it has hands-on exercises.

This is an excellent course that serves as a great introduction to spatial data science. The Instructor is obviously very knowledgable and is very enthusiastic. The course introduces a lot of material veru quickly. My only suggestion to the Instructor would be to perhaps rethink the Week 6 quiz. IMO there was not enough material presented in the course for the learner to answer several questions. Having said that, I'm glad I took the course. It was fun and I learned a lot!

This was an excellent course. I honestly thought I had pretty good handle on this topic, but I learned a lot of new concepts and applications and deepened my existing knowledge base. Furthermore, I really enjoyed the real world examples in the last section. In particular, the military infiltration example was very interesting. Thank you!

Excelente curso. Como profesional de Anal[itica de Datos y GIS me siento extremadamente feliz por haber enriquecido tanto mi conocimiento con el instructor de este curso. Muchas gracias!