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Voltar para Spatial Data Science and Applications

Comentários e feedback de alunos de Spatial Data Science and Applications da instituição Universidade Yonsei

4.4
estrelas
455 classificações

Sobre o curso

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....

Melhores avaliações

MW

13 de ago de 2018

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.

BC

5 de ago de 2021

This is a great course for persons who have interacted with GIS before. It teaches you the underlying principle and science behind most of these QGIS processing algorithms

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126 — 146 de 146 Avaliações para o Spatial Data Science and Applications

por Prudence L

25 de mar de 2019

por Ahmed L

14 de abr de 2019

por michael f

24 de ago de 2018

por Michael A

25 de ago de 2020

por Pinyo K

23 de jul de 2020

por Muhammad F K

9 de jul de 2020

por Carlos L M C

23 de nov de 2019

por Edgar L D F

6 de jan de 2021

por Andrew S

10 de mar de 2021

por Muhammad A N

26 de ago de 2020

por Jairo d S F J

20 de set de 2020

por Abhishek W

9 de abr de 2020

por Sristi S

4 de mar de 2020

por FORSI N B

11 de abr de 2020

por Milan B

15 de jan de 2020

por Uday P S B

22 de abr de 2020

por Charafeddine M

21 de nov de 2022

por adiwan F A

8 de nov de 2020

por Ahmed E

30 de dez de 2019

por CODES 4

9 de nov de 2020

por Yesi M Z A

31 de out de 2022