Spatial Data Science and Applications
Spatial (map) is regarded as the basic infrastructure of the current IT world, as evidenced by business transactions of major IT businesses such as Apple, Google, Microsoft, Amazon, Intel, and Uber, as well as automobile manufacturers such as Audi, BMW, and Mercedes. As a result, they will need to recruit more and more spatial data scientists. Based on such business trends, this course is designed to provide learners with a firm understanding of spatial data science who already have a basic understanding of data science and data analysis, and eventually to differentiate their expertise 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 to deal with spatial data science problems.
In the first week, this course will define spatial data science and explain why spatial is unique from three perspectives: business, technology, and data. The second week introduces four disciplines connected to geographic data science—GIS, DBMS, Data Analytics, and Big Data Systems—as well as the relevant open source software—QGIS, PostgreSQL, PostGIS, R, and Hadoop tools. During the third, fourth, and fifth weeks, you will master the four disciplines from the ground up, from principles to applications. In the last week, five real-world problems and their solutions were given with step-by-step techniques in an open source software environment. This is one of the best online geovisualization courses.
This course offers
- Flexible deadlines
- Shareable Certificate
- 100% online
- Intermediate Level
- It takes approximately 12 hours to complete.
- Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Coursera rating: 4.4/5
Enroll here: https://www.coursera.org/learn/spatial-data-science
