Chevron Left
Volver a Spatial Data Science and Applications

Opiniones y comentarios de aprendices correspondientes a Spatial Data Science and Applications por parte de Universidad Yonsei

4.4
estrellas
455 calificaciones

Acerca del 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....

Principales reseñas

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

Filtrar por:

76 - 100 de 147 revisiones para Spatial Data Science and Applications

por Sungha J

11 de may. de 2018

por Rajeev K

26 de sep. de 2018

por ABDUL W

7 de abr. de 2021

por Kubilay S

26 de oct. de 2020

por yasser.taufiq

5 de jul. de 2020

por Anand R

5 de nov. de 2020

por Alfredo A

29 de sep. de 2019

por Frank J A

16 de sep. de 2020

por Heena S

15 de jul. de 2020

por Fatima A A H ( O A H

29 de sep. de 2021

por Vivian F L

26 de oct. de 2020

por MUHAMMAD A B

26 de sep. de 2020

por Edier V A G

20 de jun. de 2020

por SOUGATA M

21 de abr. de 2020

por Felipe d J C H

6 de sep. de 2019

por Gulshanoy A

27 de dic. de 2021

por Priyanka C

24 de oct. de 2018

por Pornlapas S

27 de oct. de 2021

por SOUTRIK S

21 de abr. de 2020

por Manisha V

19 de may. de 2022

por sushmita g

4 de oct. de 2018

por Surendar B B

25 de jun. de 2020

por Ankur G

25 de may. de 2020

por Laurence R G A

23 de oct. de 2020

por Daniel M

4 de mar. de 2018