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Spatial Data Science and Applications

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.

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Coursera

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Yonsei University

Rating 4.2 based on 9 ratings
Length 7 weeks
Starts Dec 10 (2 days ago)
Cost $49
From Yonsei University via Coursera
Instructor Joon Heo
Free Limited Content
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Algorithms

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What people are saying

We analyzed reviews for this course to surface learners' thoughts about it

by simply watching in one review

This way, I could have learned a lot more than by simply watching the videos offered.

comprehensive introductory cause in one review

The most comprehensive introductory cause in Geo-spatial Data science .

deepened my existing in one review

I honestly thought I had pretty good handle on this topic, but I learned a lot of new concepts and applications and deepened my existing knowledge base.

e.g setting up in one review

I would have loved a more in-depth coverage with practical exercises (e.g setting up a hadoop system with MapReduce, pig, Hive).

military infiltration example in one review

In particular, the military infiltration example was very interesting.

real world examples in one review

Furthermore, I really enjoyed the real world examples in the last section.

Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile (33rd - 99th).

Data Entry 4 $34k

Data 1 $58k

Data Monitor $61k

Data Maintenance $62k

Geo-Spatial Analysis $68k

Data Architects $72k

Data Operator $74k

Geo-Spatial Technician $77k

IT Data Analyst 2 $79k

Data Integration $93k

Data Sales $100k

Data Consultant 2 $105k

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Coursera

&

Yonsei University

Rating 4.2 based on 9 ratings
Length 7 weeks
Starts Dec 10 (2 days ago)
Cost $49
From Yonsei University via Coursera
Instructor Joon Heo
Free Limited Content
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Algorithms