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Abdishakur Hassan
In this one-hour guided project, you will learn how to process geospatial data using Python. We will go through different geoprocessing tasks including how to create Geodataframes from CSV files and perform a spatial join.
Register for this course and see more details by visiting:
OpenCourser.com/course/sjkva5/analysing
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What's inside
Syllabus
Project Overview
In this one-hour guided project, you will learn how to process geospatial data using Python. We will go through different geoprocessing tasks including how to create Geodataframes from CSV files and perform a spatial join.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Suitable for absolute beginners wanting to develop practical skills in geospatial analysis
Provides a foundation in geospatial data analysis using Python
Instructed by Abdishakur Hassan, who has expertise in geospatial data analysis
Covers essential geospatial analysis tasks, including creating Geodataframes from CSV files and performing spatial joins
May require additional resources or prior knowledge in Python and geospatial analysis for a deeper understanding
Save this course
Save Analysing Covid-19 Geospatial data with Python to your list so you can find it easily later:
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Reviews summary
Engaging with geospatial
According to students, analysing Covid-19 Geospatial data with Python is an engaging course that provides detailed explanations and solid guidance from the course's instructor. Learners appreciate the thoroughness of the lectures, as well as the practical projects. While some students wish there were more advanced materials, most agree this course is a great value.
Practical projects reinforce concepts
"Good project."
"Unlike the last course I took in Coursera which the instructor only repeated the script and explained nothing."
Engaging instructor with detailed explanations
"The instructor was so good at guiding students by explaining each steps in detailed."
"He explained the reasons why we carry this specific step and showed the logic behind the processing."
"Unlike the last course I took in Coursera which the instructor only repeated the script and explained nothing."
Some wish for more advanced material
"Appreciated if included animation and additional notes ## to the steps."
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 Analysing Covid-19 Geospatial data with Python with these
activities:
Review Basic GIS Concepts
Show steps
Refresh your knowledge of basic GIS concepts to strengthen your foundation for the course.
Show steps
-
Review online resources or textbooks on GIS basics.
-
Complete practice exercises to reinforce your understanding.
Join a Study Group for Geospatial Data
Show steps
Form a study group with peers to discuss concepts, share resources, and enhance your understanding.
Browse courses on
Collaboration
Show steps
-
Find or create a study group with other students in the course.
-
Establish regular study sessions.
-
Discuss course materials, ask questions, and share insights.
Seek Mentorship from Geospatial Professionals
Show steps
Connect with geospatial professionals who can provide guidance and support in your learning journey.
Browse courses on
Mentorship
Show steps
-
Identify geospatial professionals in your network or through online platforms.
-
Reach out to potential mentors and express your interest.
-
Establish regular communication and seek advice on your learning path.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice Reading CSV Files with Geospatial Data
Show steps
Practice reading and exploring geospatial data from CSV files to strengthen your data handling skills.
Browse courses on
Geospatial Data
Show steps
-
Obtain a CSV file with geospatial data.
-
Import the CSV file into your Python environment.
-
Use Python libraries to read and display the data.
Explore GeoDataFrame Creation from CSV Files
Show steps
Follow guided tutorials to learn how to convert CSV data into GeoDataFrames for advanced geospatial analysis.
Show steps
-
Find online tutorials on creating GeoDataFrames from CSV files.
-
Follow the tutorials step-by-step.
-
Practice creating GeoDataFrames from different CSV data.
Create a Blog Post on Geospatial Data Analysis
Show steps
Create a blog post that shares your knowledge and insights on geospatial data analysis to enhance your understanding.
Browse courses on
Geospatial Analysis
Show steps
-
Choose a topic related to geospatial analysis that interests you.
-
Research and gather information on the topic.
-
Write a blog post that is informative and engaging.
-
Publish your blog post on an appropriate platform.
-
Promote your blog post on social media and other channels.
Contribute to Open Source Geospatial Projects
Show steps
Contribute to open-source geospatial projects to gain practical experience and advance your skills.
Browse courses on
Open Source
Show steps
-
Identify open-source geospatial projects that align with your interests.
-
Review the project documentation and code.
-
Suggest improvements or implement new features.
-
Submit your contributions to the project repository.
-
Collaborate with other contributors and maintain your contributions.
Review Basic GIS Concepts
Show steps
Refresh your knowledge of basic GIS concepts to strengthen your foundation for the course.
Show steps
Show steps
Show steps
- Review online resources or textbooks on GIS basics.
- Complete practice exercises to reinforce your understanding.
Join a Study Group for Geospatial Data
Show steps
Form a study group with peers to discuss concepts, share resources, and enhance your understanding.
Browse courses on
Collaboration
Show steps
Show steps
Show steps
- Find or create a study group with other students in the course.
- Establish regular study sessions.
- Discuss course materials, ask questions, and share insights.
Seek Mentorship from Geospatial Professionals
Show steps
Connect with geospatial professionals who can provide guidance and support in your learning journey.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Identify geospatial professionals in your network or through online platforms.
- Reach out to potential mentors and express your interest.
- Establish regular communication and seek advice on your learning path.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice Reading CSV Files with Geospatial Data
Show steps
Practice reading and exploring geospatial data from CSV files to strengthen your data handling skills.
Browse courses on
Geospatial Data
Show steps
Show steps
Show steps
- Obtain a CSV file with geospatial data.
- Import the CSV file into your Python environment.
- Use Python libraries to read and display the data.
Explore GeoDataFrame Creation from CSV Files
Show steps
Follow guided tutorials to learn how to convert CSV data into GeoDataFrames for advanced geospatial analysis.
Show steps
Show steps
Show steps
- Find online tutorials on creating GeoDataFrames from CSV files.
- Follow the tutorials step-by-step.
- Practice creating GeoDataFrames from different CSV data.
Create a Blog Post on Geospatial Data Analysis
Show steps
Create a blog post that shares your knowledge and insights on geospatial data analysis to enhance your understanding.
Browse courses on
Geospatial Analysis
Show steps
Show steps
Show steps
- Choose a topic related to geospatial analysis that interests you.
- Research and gather information on the topic.
- Write a blog post that is informative and engaging.
- Publish your blog post on an appropriate platform.
- Promote your blog post on social media and other channels.
Contribute to Open Source Geospatial Projects
Show steps
Contribute to open-source geospatial projects to gain practical experience and advance your skills.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Identify open-source geospatial projects that align with your interests.
- Review the project documentation and code.
- Suggest improvements or implement new features.
- Submit your contributions to the project repository.
- Collaborate with other contributors and maintain your contributions.
Career center
Learners who complete Analysing Covid-19 Geospatial data with Python will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist uses data to solve problems and make decisions. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Data Scientists who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Data Scientists working with geospatial data.
GIS Analyst
GIS Analyst
A GIS Analyst uses geographic information systems (GIS) to create and analyze maps and other visualizations. They use GIS to solve problems and make decisions about land use, natural resources, and other topics. This course may be useful for GIS Analysts who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for GIS Analysts working with geospatial data.
Crime Analyst
Crime Analyst
A Crime Analyst studies crime patterns and trends. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Crime Analysts who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Crime Analysts working with geospatial data.
Public Health Analyst
Public Health Analyst
A Public Health Analyst studies the health of a population. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Public Health Analysts who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Public Health Analysts working with geospatial data.
Remote Sensing Analyst
Remote Sensing Analyst
A Remote Sensing Analyst uses satellite imagery and other data to study the Earth's surface. They use remote sensing to monitor changes in land use, vegetation, and other features. This course may be useful for Remote Sensing Analysts who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Remote Sensing Analysts working with geospatial data.
Market Researcher
Market Researcher
A Market Researcher studies the market for products and services. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Market Researchers who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Market Researchers working with geospatial data.
Urban Planner
Urban Planner
An Urban Planner designs and plans the development of cities and towns. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Urban Planners who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Urban Planners working with geospatial data.
Environmental Scientist
Environmental Scientist
An Environmental Scientist studies the environment and its interaction with human activity. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Environmental Scientists who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Environmental Scientists working with geospatial data.
Transportation Planner
Transportation Planner
A Transportation Planner plans and designs transportation systems, such as roads, highways, and public transportation. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Transportation Planners who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Transportation Planners working with geospatial data.
Insurance Analyst
Insurance Analyst
An Insurance Analyst studies insurance risks and trends. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Insurance Analysts who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Insurance Analysts working with geospatial data.
Geographer
Geographer
A Geographer studies the physical features of the Earth and the human activity that takes place on it. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Geographers who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Geographers working with geospatial data.
Business Analyst
Business Analyst
A Business Analyst uses data to analyze and solve business problems. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Business Analysts who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Business Analysts working with geospatial data.
Financial Analyst
Financial Analyst
A Financial Analyst studies financial markets and trends. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Financial Analysts who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Financial Analysts working with geospatial data.
Marketing Analyst
Marketing Analyst
A Marketing Analyst studies marketing campaigns and trends. They use a variety of tools to analyze and interpret data, including geospatial data. This course may be useful for Marketing Analysts who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Marketing Analysts working with geospatial data.
Epidemiologist
Epidemiologist
An Epidemiologist researches the causes of disease and other health problems in populations. Their work helps to create effective public health policies to prevent and control diseases. This course may be useful for Epidemiologists who are interested in using Python for geospatial data analysis. The course covers how to create Geodataframes from CSV files and perform a spatial join, which are both skills that can be useful for Epidemiologists working with geospatial data.
For more career information including salaries, visit:
OpenCourser.com/course/sjkva5/analysing
Reading list
We've selected nine 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
Analysing Covid-19 Geospatial data with Python.
This comprehensive guide provides a thorough foundation in geospatial analysis techniques, algorithms, and applications. It covers topics ranging from data acquisition and preprocessing to spatial statistics and modeling, making it an essential reference for this course.
Comprehensive guide to spatial data analysis with R. It covers a wide range of topics, including data exploration, statistical analysis, and visualization. It also includes a number of case studies that show you how to use R to solve real-world problems.
This practical guide focuses specifically on using Python for geospatial data analysis and development. It covers topics such as data manipulation, spatial operations, and web mapping, which directly align with the hands-on Python component of this course.
Gentle introduction to geospatial analysis with Python. It covers the basics of geospatial data, including data types, coordinate systems, and projections. It also includes a number of exercises that help you practice your skills.
Gentle introduction to geospatial analysis with Python. It covers the basics of geospatial data, including data types, coordinate systems, and projections. It also includes a number of exercises that help you practice your skills.
This comprehensive text provides a detailed overview of digital mapping technologies. It covers topics such as data acquisition, processing, and visualization, which can provide a deeper understanding of the underlying technologies used in geospatial data analysis.
This comprehensive text provides a solid foundation in statistical learning and data mining techniques. It covers topics such as regression, classification, and unsupervised learning, which can be beneficial for those interested in applying statistical models to geospatial data.
This practical guide provides a valuable overview of data science concepts and applications in a business context. It covers topics such as data management, data analysis, and machine learning, which can provide additional insights for those interested in the intersection of geospatial data and business intelligence.
This specialized book focuses on using R for geospatial data analysis. It covers topics such as data manipulation, spatial statistics, and web mapping, which provide an alternative perspective to the Python-based approach in this course.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/sjkva5/analysing
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Effort
1.5 hours
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Abdishakur Hassan
Language
English
Good to know
Suitable for absolute beginners wanting to develop practical skills in geospatial analysis
Provides a foundation in geospatial data analysis using Python
Instructed by Abdishakur Hassan, who has expertise in geospatial data analysis
Covers essential geospatial analysis tasks, including creating Geodataframes from CSV files and performing spatial joins
May require additional resources or prior knowledge in Python and geospatial analysis for a deeper understanding
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