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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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1 — 25 de 146 Avaliações para o Spatial Data Science and Applications

por Jesús A

7 de jun de 2019

por Kumar R

27 de jul de 2019

por rustom s

8 de abr de 2018

por Zack D

8 de jun de 2018

por Julia H

17 de abr de 2020

por CHESSEL P

16 de jul de 2019

por Gopinath P

3 de set de 2019

por Tino K

3 de fev de 2021

por Pankaj W

7 de dez de 2019

por AMAN T

6 de abr de 2020

por Michael B

10 de jun de 2018

por MONCADA S J F

18 de jun de 2020

por Keith P C L

15 de set de 2020

por Ahmed W M

2 de mai de 2020

por Daniel L

4 de abr de 2018

por Stanislava G

6 de ago de 2018

por Satish M

2 de mar de 2019

por Raffi I

13 de ago de 2020

por Allyson D d L

17 de out de 2021

por Gabriel A F G

22 de ago de 2020

por Gary C

20 de mar de 2022

por Jaya S S

12 de set de 2020

por Rodrigo V

24 de nov de 2018

por Bopitiye G U N K

14 de nov de 2020

por Priyantha B K

2 de nov de 2020