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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
433 classificações
138 avaliações

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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76 — 100 de 136 Avaliações para o Spatial Data Science and Applications

por Vivian F L

26 de Out de 2020

informative!

por MUHAMMAD A B

26 de Set de 2020

Great course

por Edier V A G

20 de Jun de 2020

very good

por SOUGATA M

21 de Abr de 2020

VERY NICE

por Felipe d J C H

6 de Set de 2019

Excellent

por Gulshanoy A

27 de Dez de 2021

Perfect!

por Priyanka C

24 de Out de 2018

Awesome

por Pornlapas [ S

27 de Out de 2021

g​ood

por SOUTRIK S

21 de Abr de 2020

GREAT

por sushmita g

4 de Out de 2018

.

por Surendar B B

25 de Jun de 2020

I am a postgraduate and so far I have been practising only Desktop GIS and Spatial data analysis. Through this course, I got the insights of Server GIS world and the significance of Spatial Big Data System in the real-world applications. I consider this as a significant step towards my Data Science career.

The course content is reliable and outstanding.

Content delivery and presentations were deliberately comprehensible.

The only limitation was the hands-on presentation was inadequate.

Anyway, this is a great course, and I was delighted.

Thanks,

por Ankur G

25 de Mai de 2020

The Course is awesome to get knowledge of data science wih spatial data. But this is only theoretical course i mean only those who have understanding of GIS can enroll this course before learning data science since it gives clear pictures of all required aspects of spatial data science. I am little fed up because lots of theory covered, Some of the units may be removed to get practical in this course. By the way if you need only knowledge of spatial data science & related very sound vocabulary this is the course for you.

por Laurence R G A

23 de Out de 2020

When i enrolled here i thought it would be easy due to my background GIS, however i was wrong it tackled on a range of different topics that was very new to me but i was already facing in real life. It also showed the connections of each and every one of the functioning parts within the spatial data science. Overall it was an excellent course since it showed me new concepts and interplay of different spatial data systems and how can it be used.

por Daniel M

4 de Mar de 2018

The course offers a good overview and is very compact. I would have loved a more in-depth coverage with practical exercises (e.g setting up a hadoop system with MapReduce, pig, Hive). This way, I could have learned a lot more than by simply watching the videos offered. Further, please provide the well designed slides for download. I already posted this request in the course forum, but the forum doesn't seem to be used (no answers at all).

por Vignesh T

12 de Jun de 2019

This course is an fantastic introduction on Spatial Big Data Management and Analytics. It had given me a strong understanding of the various opensource tools and concepts for spatial data science. I would strongly recommend others to undergo the course as an Introduction to spatial data science and applications. However, one has to learn many other programming languages such as Hive, Pig and Sqoop to master spatial big data.

por Prabuddha D B

11 de Mar de 2021

This is an introductory course of spatial data science. Various technologies will be introduced but no hand on experience given. The given information can be used as starting point for learning spatial data science

Only take this course if you are already familiar with some GIS (QGIS/ ArcGIS) , database management & spatial analyst as this course will introduce many concepts/ theories

por Nils K

30 de Out de 2018

Good quick overview of the discipline. No practical tests. As such I could complete the course in 2 1/2 days. Given the extent of the whole discipline, it is probably impossible to present this in one course. Maybe would need a specialisation. But good info to get you started on filling possible knowledge gaps.

por Sina N A

24 de Out de 2020

this course illustrated the main structure of Spatial Data Analysis. this was useful for getting a general knowledge about different part of spatial data analysis and their connectivity. but if it suggested a relative courses or documents for following and concentrating on each ones, i would appreciate that

por Pradip S

12 de Ago de 2020

A superficial insight into spatial data learning with comprehensive theoretical concepts and explanations. Although hand-on exercises and deeper applications could have made this course more applicable and thoroughgoing. Overall, this course serves as a pathways into the realm of spatial data science.

por Isaiah M

22 de Mai de 2021

I had such an amazing time from the very first lecture, I think it was worth it, I look forward to a more practical course that would allow participants to gain valuable experience, build confidence and skills needed to start off in the spatial science industry. Thank you for the exposure.

por Jefferson R V J

4 de Out de 2020

The topics were easy to understand even at its complexity. I think after completing this course I will consider Spatial Data Science as a field for me to specialize. Thanks to DOST of the Philippines for the support and also to Prof. Joon for this course and to the Coursera team.

por Yuan L

15 de Jun de 2020

The course materials are rich and comprehensive. However, there is a lack of hands-on practice. Besides, the majority of the materials require some experience in the field to truly understand their significance.

por Antonio M M

29 de Set de 2020

I think the course gives good bases to understand the spatial data science but will be better if this includes some practical excercises that allow to understand and put on practice the acquired knowledge

por Marino M

11 de Jul de 2019

El curso presenta muchos conceptos teóricos interesantes que abren todo un campo nuevo de aprendizaje, los ejemplos de aplicación son buenos pero podrían profundizar mejor en los ejemplos.

por Guillaume R

5 de Jun de 2018

Really interesting course, well structured. Including practical work ( setting up the tools, writing code or conducting some analysis) would have made of it the best MOOC ever made.