Spatial Data Science and Applications

( 48 Reviews )

Created by: Joon Heo

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Course Depth & Coverage

Overall Score : 88 / 100

Course Description

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.

Time: 14h

Instructor Details

Joon Heo

4.4 Rating
48 Reviews

Joon Heo is a professor at the department of civil and environmental engineering, and the director of Open and Smart Education (OSE) Center, which was formed in 2014 and in charge of MOOC production, Yonsei Learning Management System (YSCEC), and other educational issues. He also served as an associate director of Yonsei Enterprise Support (YES) Foundation from 2009 to 2017, which is in charge of incubating and accelerating start-ups at Yonsei University. He obtained his B.S. in the Department of Civil Engineering (Urban Engineering Major) from the Seoul National University in 1993, and his M.S. and Ph.D. in Civil and Environmental Engineering from University of Wisconsin-Madison in 1997 and 2001 respectively. In 2000, he joined a start-up company, Forest One Inc., a value-added geospatial information provider and IT consulting company, located in Evanston, IL. For the following five years, he leaded technology developments as CTO and provided technical services to Fortune 500 companies. He joined the Department of Civil and Environmental Engineering at Yonsei University in 2005 as a faculty member and has taught Geographic Information System (GIS), photogrammetry, and remote sensing. His areas of research interests include (1) spatial data production and analytics with specific domain expertise of infrastructure operation and management; (2) spatial data science with applications of transportation, health, business, military, and education; (3) image processing and remote se

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By Imoh E on 5-Jul-19

very insightful and impacting session laced with applicable examples and contemporary issues. Thank you coursera. Thank you Yonsei University.

By Zack D on 8-Jun-18

Overall good course. Rated as intermediate but more beginner in my opinion. Lots of overlap with what i would expect in an 'vanilla' data science course. If youve taken anything like that expect to hear alot of things you have heard before but does thuroughly extend in to the spatial aspect and application.I would have perferred a little more emphasis on analysis techniques and deeper applications. I was also suprised by no direct application of for the student at all. all video based no hands on.Last couple of quizes are also pretty tough, mostly from the fact that they are poorly written and difficult to answer from an infromed perspective.

By Satish M on 2-Mar-19

The course was very knowledgeable. But there were some lack of practical exercises. The students should have been provided with the basic tutorial of the software. We have learned many things in theory but not practically. Overall I rate it 3 out of 5.

By Irina R on 30-Oct-19

clear presentations and good examples

By Vignesh T on 12-Jun-19

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.

By Marino M on 11-Jul-19

El curso presenta muchos conceptos teÃƒÂ³ricos interesantes que abren todo un campo nuevo de aprendizaje, los ejemplos de aplicaciÃƒÂ³n son buenos pero podrÃƒÂan profundizar mejor en los ejemplos.

By Ahmed L on 15-Apr-19

Good lead to Spatial Data Science

By Nils K on 30-Oct-18

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.

By michael f on 24-Aug-18

Good to understand the concepts

By Stanislava G on 6-Aug-18

Very good overview of tools used for Spatial Data Science and explained their benefits and limitations for many real-life problems. Applications are shown on examples using real-life data, and it also provides a few good tips for external resources. Some hands-on exercises would be nice.

By Arnold k R on 19-Mar-18