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Отзывы учащихся о курсе Spatial Data Science and Applications от партнера Университет Ёнсе

Оценки: 391
Рецензии: 130

О курсе

Spatial (map) is considered as a core infrastructure of modern IT world, which is substantiated by business transactions of major IT companies such as Apple, Google, Microsoft, Amazon, Intel, and Uber, and even motor companies such as Audi, BMW, and Mercedes. Consequently, they are bound to hire more and more spatial data scientists. Based on such business trend, this course is designed to present a firm understanding of spatial data science to the learners, who would have a basic knowledge of data science and data analysis, and eventually to make their expertise differentiated from other nominal data scientists and data analysts. Additionally, this course could make learners realize the value of spatial big data and the power of open source software's to deal with spatial data science problems. This course will start with defining spatial data science and answering why spatial is special from three different perspectives - business, technology, and data in the first week. In the second week, four disciplines related to spatial data science - GIS, DBMS, Data Analytics, and Big Data Systems, and the related open source software's - QGIS, PostgreSQL, PostGIS, R, and Hadoop tools are introduced together. During the third, fourth, and fifth weeks, you will learn the four disciplines one by one from the principle to applications. In the final week, five real world problems and the corresponding solutions are presented with step-by-step procedures in environment of open source software's....

Лучшие рецензии

13 авг. 2018 г.

Great course. It helps I have a background in both Data Science and Geographic Information Science, but still found it equally interesting and challenging! I would highly recommend this course.

4 июля 2019 г.

very insightful and impacting session laced with applicable examples and contemporary issues. Thank you coursera. Thank you Yonsei University.

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126–128 из 128 отзывов о курсе Spatial Data Science and Applications

автор: Raffi I

13 авг. 2020 г.

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.

автор: Javier F M S

18 июня 2020 г.

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?)

автор: Tino K

3 февр. 2021 г.

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!