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Geospatial APIs For Data Science Applications In Python

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  • Are you currently enrolled in any of my GIS and remote sensing related courses?

  • Or perhaps you have prior experiences in GIS or tools like R and QGIS?

  • You want to quickly analyse large amounts of geospatial data

  • Implement machine learning models on remote sensing data

  • You don't want to spend 100s and 1000s of dollars on buying commercial software for imagery analysis?

  • You want to have access  to a multi-petabyte catalogue of satellite imagery and geospatial datasets with planetary-scale analysis capabilities

The next step for you is to gain proficiency in obtaining free geospatial datasets from a variety of sources, from Foursquare to Google Earth Engine via their Python-friendly APIs and analyse these using data science techniques

 .

My course provides a foundation to carry out  By taking this course, you are taking an important step forward in your GIS journey to become an expert in geospatial analysis.

Why Should You Take My Course?

I have an MPhil (Geography and Environment) from the University of Oxford, UK. I also completed a PhD at Cambridge University (Tropical Ecology and Conservation).

I have several years of experience in analyzing real-life spatial geospatial data from different sources and producing publications for international peer-reviewed journals.

In this course, actual geospatial data obtained via Foursquare and GEE APIs will be used to give you hands-on experience of applying data science and machine learning techniques to these data to answer real-life questions such as identifying the best locations for a restaurant or changes in socio-economic dynamics of a territory.

This course will ensure you learn & put geospatial data analysis into practice today and increase your proficiency in using APIs for obtaining these data and deriving valuable insights from them.

This is a fairly comprehensive course, i.e. we will focus on learning the most essential and widely encountered data science techniques applied to geospatial data

In addition to all the above, you’ll have 

ENROLL NOW :)

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Good to know

Know what's good
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, and possible dealbreakers
Covers learning how to obtain free geospatial datasets from various sources like Foursquare and Google Earth Engine
Teaches how to analyze large amounts of geospatial data using data science techniques
Provides hands-on experience in applying data science and machine learning techniques to actual geospatial data
Helps learners gain proficiency in using APIs for obtaining geospatial data and deriving valuable insights
Focuses on essential and widely encountered data science techniques applied to geospatial data
Taught by an experienced instructor with a strong academic background in geospatial analysis

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Career center

Learners who complete Geospatial APIs For Data Science Applications In Python will develop knowledge and skills that may be useful to these careers:
Geospatial Analyst
Geospatial Analysts play a central role in analyzing and interpreting geospatial data to derive meaningful insights and help organizations make informed decisions. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for Geospatial Analysts. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Geospatial Analysis.
Data Scientist
Data Scientists analyze large amounts of data to identify patterns and trends, and develop predictive models. This course provides a foundation in data science techniques applied to geospatial data, which can be highly valuable for Data Scientists. By gaining proficiency in using APIs for obtaining geospatial data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Data Science.
GIS Analyst
GIS Analysts use geographic information systems (GIS) to analyze and visualize geospatial data. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for GIS Analysts. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in GIS Analysis.
Remote Sensing Analyst
Remote Sensing Analysts use satellite imagery and other remote sensing data to monitor and analyze the Earth's surface. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for Remote Sensing Analysts. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Remote Sensing Analysis.
Geospatial Developer
Geospatial Developers build and maintain geospatial applications. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for Geospatial Developers. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Geospatial Development.
Business Analyst
Business Analysts use data to analyze and improve business processes. This course provides a foundation in data science techniques applied to geospatial data, which can be highly valuable for Business Analysts. By gaining proficiency in using APIs for obtaining geospatial data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Business Analysis.
Urban Planner
Urban Planners design and plan the development of cities and towns. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for Urban Planners. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Urban Planning.
Environmental Scientist
Environmental Scientists study the environment and its components. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for Environmental Scientists. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Environmental Science.
Geographer
Geographers study the Earth's surface and its human and environmental interactions. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for Geographers. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Geography.
Cartographer
Cartographers create maps and other visual representations of geographic information. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for Cartographers. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Cartography.
Surveyor
Surveyors measure and map the Earth's surface. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for Surveyors. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Surveying.
Hydrologist
Hydrologists study water and its movement on, above, and below the Earth's surface. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for Hydrologists. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Hydrology.
Geologist
Geologists study the Earth's composition, structure, and history. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for Geologists. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Geology.
Oceanographer
Oceanographers study the oceans and their physical, chemical, and biological properties. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which can be highly valuable for Oceanographers. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Oceanography.
Geophysicist
Geophysicists study the Earth's physical properties and processes. This course provides a foundation in obtaining free geospatial datasets from a variety of sources and analyzing them using data science techniques, which may be useful for Geophysicists. By gaining proficiency in using APIs for obtaining these data and deriving valuable insights from them, learners of this course can enhance their skills and advance their careers in Geophysics.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Geospatial APIs For Data Science Applications In Python.
Valuable reference for anyone who is interested in using Python for data science. It covers all the basics of Python, as well as more advanced topics such as data wrangling, data analysis, and machine learning.
Provides a practical guide to using geostatistics for spatial data analysis. It covers a wide range of topics, from basic concepts to more advanced topics such as spatial interpolation and kriging.
Provides a comprehensive overview of spatial statistics. It covers a wide range of topics, from basic concepts to more advanced topics such as spatial regression and spatial autocorrelation.
This classic textbook provides a comprehensive overview of remote sensing and image interpretation. It covers a wide range of topics, from basic concepts to more advanced topics such as image processing and classification.
This classic textbook provides a comprehensive overview of digital image processing. It covers a wide range of topics, from basic concepts to more advanced topics such as image enhancement and restoration.
Provides a practical guide to using geospatial technologies. It covers a wide range of topics, from basic concepts to more advanced topics such as spatial analysis and geostatistics.
This classic textbook provides a comprehensive overview of GIS. It covers a wide range of topics, from basic concepts to more advanced topics such as spatial analysis and geostatistics.
Provides a comprehensive overview of using remote sensing data for geospatial analysis. It covers topics such as data acquisition, processing, and visualization.
Provides overview of Geospatial Analysis. It introduces the fundamental concepts of geospatial analysis, including data acquisition, processing representation, and modeling . This book is useful for background and as a reference book.
Gentle introduction to R. It covers topics such as data types, variables, and control flow with a focus on using R for data science.
Gentle introduction to machine learning. It covers topics such as data preparation, model selection, and model evaluation with a focus on using open-source software.
Gentle introduction to data science. It covers topics such as data acquisition, processing, and visualization with a focus on using open-source software.

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