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Shaowen Wang
and
Anand Padmanabhan
This course is intended to introduce students to CyberGIS—Geospatial Information Science and Systems (GIS)—based on advanced cyberinfrastructure as well as the state of the art in high-performance computing, big data, and cloud computing in the context of geospatial data science. Emphasis is placed on learning the cutting-edge advances of cyberGIS and its underlying geospatial data science principles.
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What's inside
Syllabus
Course Orientation
You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.
Read more
Syllabus
Course Orientation
You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Develops core skills needed to apply cutting-edge advances of CyberGIS in contemporary geospatial data science industry and/or academic research
Taught by leading experts Shaowen Wang and Anand Padmanabhan
Strong focus on theoretical foundations of CyberGIS
Provides an introduction to taming big data
Covers cutting-edge topics not found in many other courses
Coursework requires students to come in with basic geospatial data science background knowledge
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Reviews summary
Foundational cybergis with practical python & big data
According to learners, "Getting Started with CyberGIS" offers a largely positive introduction to the field, particularly for those looking to understand how high-performance computing and big data intersect with traditional GIS. Students found the lectures clear and engaging, appreciating the blend of theoretical foundations and practical Python examples. Specific strengths include the practical geospatial visualization using Python (Modules 2 and 3), with tools like GeoPandas, Folium, Shapely, and RasterIO being highly valued. However, some learners noted a significant challenge with environment setup, especially for Module 3's Hadoop section, which was also described as somewhat rushed. A common concern was that the course implicitly assumes prior Python knowledge, potentially misleading those new to programming.
Provides a strong conceptual understanding of CyberGIS principles.
"The lectures were clear, and the examples... were very helpful. I found the theoretical foundations in Module 4 to be well-explained."
"The conceptual parts were excellent and clarified a lot about CyberGIS."
"It gave me a good grasp of the theoretical framework and current applications of CyberGIS."
Offers hands-on experience with key geospatial Python libraries.
"Module 2 on Python visualization was very practical and I appreciated the hands-on labs."
"I particularly liked the introduction to GeoPandas and Folium in Module 2."
"The practical exercises solidified my understanding, especially the work with Shapely and RasterIO."
Explores cutting-edge CyberGIS topics crucial for modern data science.
"Excellent course! The content is highly relevant for anyone looking into advanced geospatial data science."
"As a GIS professional, I found this course invaluable for understanding how high-performance computing and big data intersect with traditional GIS."
"It's a challenging but rewarding course, providing valuable insight into handling big geospatial data."
The big data section on Hadoop is considered too short for its complexity.
"The Hadoop part was interesting but I couldn't get the examples to run on my local machine. The Hadoop part was too brief for its complexity."
"The Hadoop section felt a little rushed."
Course content assumes a certain level of Python programming expertise.
"The 'getting started' title is misleading. You need a strong background in Python and possibly even some basic GIS knowledge to keep up."
"I enjoyed this course... but I had some prior experience with Python which helped significantly. Newcomers to Python might struggle."
"I struggled immensely with the practical Python labs. It felt like they assumed a higher level of programming expertise."
Learners frequently face issues setting up the necessary development environments.
"Setting up the environment for Module 3 was a bit challenging, and the Hadoop section felt a little rushed."
"The setup instructions were not clear for many of the tools, and I spent more time debugging my environment than learning."
"The practical exercises required a lot of independent problem-solving for environment setup, which was frustrating."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Getting Started with CyberGIS with these
activities:
Practice with GeoPandas
Show steps
Practice using GeoPandas to strengthen your understanding of geospatial object manipulation.
Browse courses on
GeoPandas
Show steps
-
Install GeoPandas
-
Load a spatial dataset into a GeoDataFrame
-
Perform basic spatial operations (e.g., buffer, dissolve, union)
Tutorial on Geospatial Visualization with Python
Show steps
Follow a tutorial to enhance your skills in visualizing geospatial data using Python libraries such as Matplotlib and Cartopy.
Browse courses on
Geospatial Visualization
Show steps
-
Set up the required Python environment
-
Import the necessary libraries
-
Create a map using Matplotlib and Basemap
-
Style the map using Cartopy
Exercises on Hadoop Fundamentals
Show steps
Complete exercises on Hadoop fundamentals to reinforce your understanding of its architecture, components, and functionalities.
Browse courses on
Hadoop
Show steps
-
Install Hadoop and set up a Hadoop cluster
-
Write a simple MapReduce program
-
Run the program on a Hadoop cluster and analyze the results
Two other activities
Expand to see all activities and additional details
Show all five activities
Build a Web Map with GeoJSON
Show steps
Create a web map using GeoJSON to gain hands-on experience in sharing and visualizing geospatial data on the web.
Browse courses on
Web Mapping
Show steps
-
Prepare your geospatial data in GeoJSON format
-
Create a web mapping application using a library like Leaflet or OpenLayers
-
Deploy the web map on a platform like GitHub Pages
Project: Develop a Geospatial Application
Show steps
Embark on a project to build a geospatial application, integrating concepts from CyberGIS and Geospatial Data Science, to address a real-world problem.
Show steps
-
Identify a problem that can be addressed with geospatial data and analysis
-
Design and plan the application
-
Implement the application using appropriate geospatial tools and libraries
-
Test and evaluate the application's functionality and performance
-
Deploy the application and share it with others
Practice with GeoPandas
Show steps
Practice using GeoPandas to strengthen your understanding of geospatial object manipulation.
Browse courses on
GeoPandas
Show steps
Show steps
Show steps
- Install GeoPandas
- Load a spatial dataset into a GeoDataFrame
- Perform basic spatial operations (e.g., buffer, dissolve, union)
Tutorial on Geospatial Visualization with Python
Show steps
Follow a tutorial to enhance your skills in visualizing geospatial data using Python libraries such as Matplotlib and Cartopy.
Browse courses on
Geospatial Visualization
Show steps
Show steps
Show steps
- Set up the required Python environment
- Import the necessary libraries
- Create a map using Matplotlib and Basemap
- Style the map using Cartopy
Exercises on Hadoop Fundamentals
Show steps
Complete exercises on Hadoop fundamentals to reinforce your understanding of its architecture, components, and functionalities.
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Install Hadoop and set up a Hadoop cluster
- Write a simple MapReduce program
- Run the program on a Hadoop cluster and analyze the results
Two other activities
Expand to see all activities and additional details
Show all five activities
Build a Web Map with GeoJSON
Show steps
Create a web map using GeoJSON to gain hands-on experience in sharing and visualizing geospatial data on the web.
Browse courses on
Web Mapping
Show steps
Show steps
Show steps
- Prepare your geospatial data in GeoJSON format
- Create a web mapping application using a library like Leaflet or OpenLayers
- Deploy the web map on a platform like GitHub Pages
Project: Develop a Geospatial Application
Show steps
Embark on a project to build a geospatial application, integrating concepts from CyberGIS and Geospatial Data Science, to address a real-world problem.
Show steps
Show steps
Show steps
- Identify a problem that can be addressed with geospatial data and analysis
- Design and plan the application
- Implement the application using appropriate geospatial tools and libraries
- Test and evaluate the application's functionality and performance
- Deploy the application and share it with others
Career center
Learners who complete Getting Started with CyberGIS will develop knowledge and skills
that may be useful to these careers:
Geospatial Data Analyst
Geospatial Data Analyst
Geospatial Data Analysts are responsible for collecting, managing, analyzing, and interpreting geospatial data. They use their knowledge of GIS and data science to solve problems and make informed decisions. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Geospatial Data Analysts.
Geospatial Developer
Geospatial Developer
Geospatial Developers are responsible for designing, developing, and maintaining geospatial applications. They use their knowledge of GIS and programming to create tools and solutions that help users visualize, analyze, and interact with geospatial data. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Geospatial Developers.
GIS Manager
GIS Manager
GIS Managers are responsible for overseeing the implementation and use of GIS technology within an organization. They work with users to identify needs, develop strategies, and implement solutions. This course provides a strong foundation in CyberGIS, which is essential for managing big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for GIS Managers.
Geospatial Scientist
Geospatial Scientist
Geospatial Scientists use their knowledge of GIS and data science to study the Earth's surface. They use geospatial data to identify patterns, trends, and relationships. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Geospatial Scientists.
Urban Planner
Urban Planner
Urban Planners use their knowledge of GIS and planning to design and manage cities and towns. They use geospatial data to identify problems and opportunities, and to develop plans for future development. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Urban Planners.
Environmental Scientist
Environmental Scientist
Environmental Scientists use their knowledge of GIS and environmental science to study the environment. They use geospatial data to identify and assess environmental problems, and to develop solutions. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Environmental Scientists.
Transportation Planner
Transportation Planner
Transportation Planners use their knowledge of GIS and transportation planning to design and manage transportation systems. They use geospatial data to identify problems and opportunities, and to develop plans for future development. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Transportation Planners.
Land Surveyor
Land Surveyor
Land Surveyors use their knowledge of GIS and surveying to measure and map land. They use geospatial data to create accurate maps and plans. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Land Surveyors.
Geospatial Intelligence Analyst
Geospatial Intelligence Analyst
Geospatial Intelligence Analysts use their knowledge of GIS and intelligence analysis to analyze geospatial data. They use geospatial data to identify and assess threats, and to develop strategies for应对. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Geospatial Intelligence Analysts.
GIS Technician
GIS Technician
GIS Technicians use their knowledge of GIS to create and maintain maps and other geospatial data. They use geospatial data to support a variety of applications, such as planning, engineering, and environmental management. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for GIS Technicians.
Data Scientist
Data Scientist
Data Scientists use their knowledge of statistics, machine learning, and data mining to analyze data and extract insights. They use data to solve problems, make predictions, and develop new products and services. This course may be helpful for Data Scientists who want to learn about CyberGIS and its applications in geospatial data science.
Software Engineer
Software Engineer
Software Engineers use their knowledge of computer science to design, develop, and maintain software applications. They use software to solve problems, improve efficiency, and create new products and services. This course may be helpful for Software Engineers who want to learn about CyberGIS and its applications in geospatial data science.
Computer Scientist
Computer Scientist
Computer Scientists use their knowledge of computer science to study the theory and practice of computation. They develop new algorithms and theories to solve problems and improve the efficiency of computing systems. This course may be helpful for Computer Scientists who want to learn about CyberGIS and its applications in geospatial data science.
Statistician
Statistician
Statisticians use their knowledge of statistics to collect, analyze, and interpret data. They use statistics to solve problems, make predictions, and develop new products and services. This course may be helpful for Statisticians who want to learn about CyberGIS and its applications in geospatial data science.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their knowledge of mathematics and computer science to solve problems in a variety of industries. They use mathematical models to analyze data, identify inefficiencies, and develop solutions to improve operations. This course may be helpful for Operations Research Analysts who want to learn about CyberGIS and its applications in geospatial data science.
For more career information including salaries, visit:
OpenCourser.com/course/v1pqn5/getting
Reading list
We've selected six 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
Getting Started with CyberGIS.
Comprehensive guide to geocomputation with R. It covers a wide range of topics, from basic data manipulation to advanced spatial analysis.
Save
Is very comprehensive covering all aspects of geospatial analysis from data to applications. While it is more advanced than what the course covers, it can serve as a future reference to learn about more advanced topics in geospatial analysis with a fit score of 80.
Introduces the concepts of big data, storage, and analytics technologies in the cloud with a focus on Mapreduce computations. As the course covers Hadoop and its Mapreduce functionalities, this book would be a great reference text to learn more, with a fit score of 80.
Comprehensive guide to Hadoop. It covers a wide range of topics, from basic concepts to advanced administration.
Comprehensive guide to geospatial information science and technology. It covers a wide range of topics, from basic concepts to advanced applications.
Save
Comprehensive guide to GIS fundamentals. It covers a wide range of topics, from basic concepts to advanced applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/v1pqn5/getting
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Effort
4-weeks of study, 4 Hrs a week
Level
Introductory
Via
Coursera
Institution
University of Illinois at Urbana-Champaign
Instructors
Shaowen Wang
Anand Padmanabhan
Language
English
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