greate.

genial

The course brings an introduction to Spatial Data Science with definitions and presentations of methods for solving problems. Nevertheless, it would be better if it may present the concrete step by step applications of those methods to simpler problems. I learned a lot, and as usual, I realized that I need to learn more and more. Thanks a lot Prof Heo, Yonsei University and Coursera.

Teaches some good concepts, but does not show full workflows (no opportunity to replicate/ follow along). R code was mentioned, but not shown. :( Has numerous grammatical and spelling errors which could have been prevented with simple spelling & grammar checks in Microsoft Word.

The topics covered in this course are very complex and interesting. Several open-source software were introduced yet there is no hands-on training. Overall, this course is good to give students an understanding of spatial data science.

The course scratches all the areas of Spatial Data Science, overviewing techniques and use cases. Don't expect to learn the tools. Even though it explain the foundations of some tools, it won't teach you how to use them.

Course contents are very relevant to the industry, but the course lack in hands-on tutorials of various spatial data science tools. The tutor should himself go through the tools for the students during the course.

The course was quite good for getting the introductory knowledge about spatial data science and its related domain . However, it lacks some practicals work to be done by the enroller itself. Thanks

Rich course. However, i expected to see more. I expected to learn how to better manipulate QGIS but the course is entirely theoretical

Good high level overview of spatial data science but the course would have been much better with a hand-on instruction!

Very Informative but lacks hands-on practice or assignments

Need hands-on to use the software

need more practicality

Nice Course

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.

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.