Yonsei - Spatial Data Science and Applications
- Offered byCoursera
Spatial Data Science and Applications at Coursera Overview
Duration | 12 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Spatial Data Science and Applications at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Intermediate Level
- Approx. 12 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Spatial Data Science and Applications at Coursera Course details
- 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.
Spatial Data Science and Applications at Coursera Curriculum
Understanding Spatial Data Science
Introduction to the course
1.1 Introduction to Spatial Data Science
1.2 Why is Spatial Special? (I) - A Business Perspective
1.3 Why is Spatial Special? (II) - A Technical Perspective
1.4 Why is Spatial Special? (III) - A Data Perspective
Understanding Spatial Data Science
Solution Structures of Spatial Data Science Problems
Four Disciplines for Spatial Data Science and Applications
Open Source Software's
Spatial Data Science Problems
Spatial Data vs. Spatial Big Data
QGIS vs. ArcGIS
What is spatial Big Data?
Solution Structures of Spatial Data Science Problems
Geographic Information System (GIS)
Five Layers of GIS
Spatial Reference Framework
Spatial Data Models
Spatial Data Acquisition
Spatial Data Analysis
Geo-visualization and Information Delivery
Sources of Spatial Data
Making Sense of Maps
Geographic Information System (GIS)
Spatial DBMS and Big Data Systems
Database Management System (DBMS)
Spatial Database Management System (SDBMS)
Big Data System ? MapReduce
Big Data System ? Hadoop
Hadoop Ecosystem
Spatial Big Data Systems
DBMS vs. MapReduce
Spatial DBMS and Big Data Systems
Spatial Data Analytics
Spatial Data Analytics
Proximity and Accessibility
Spatial Autocorrelation
Spatial Interpolation
Spatial Categorization
Hotspot Analysis
Network Analysis
Starbucks GIS
Happy Maps
Spatial Data Analytics
Practical Applications of Spatial Data Science
Desktop GIS - Finding Optimal Counties for Timber Investment
Server GIS - An Integration of Municipal Spatial Databases
Spatial Data Analytics I - Influential Variables of Regional Disease Prevalence Rate
Spatial Data Analytics II - Military Infiltration Route Analysis
Spatial Big Data Management and Analytics - Taxi Trajectory Analysis for Finding Pick-up Hotspots
Infiltration route analysis using Thermal Observation Devices
Practical Application of Spatial Data Science
Spatial Data Science and Applications at Coursera Admission Process
Important Dates
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