We may earn an affiliate commission when you visit our partners.

Survey of python for GIS applications

4.4

Based on 240 ratings

, see reviews

This course covers the basics of the python language, the python language, and the core python packages for data analysis, especially of geospatial data. The goal of the course is to provide a broad introduction to the capabilities of python and how all the various packages work together. This will provide a starting point for deeper exploration on your own or in future courses.

Read more

This course covers the basics of the python language, the python language, and the core python packages for data analysis, especially of geospatial data. The goal of the course is to provide a broad introduction to the capabilities of python and how all the various packages work together. This will provide a starting point for deeper exploration on your own or in future courses.

Introduction to python
Object oriented python
Packages and modules
Unit tests
Jupyter notebooks
Numpy
Matplotlib
Pandas
Fiona and shapely
Geopandas
Rasterio
Geocoding
PyQt

Or start a personal plan

And upskill with Udemy

Here's a deal for you

Save money when you learn with a deal that may be relevant to this course.

All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

Only 10 hours left!

24-Hour Flash Sale

Close your skills gaps with online courses and save big for a limited time.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Explores essential geospatial analysis packages for Python, including NumPy, Matplotlib, Pandas, Fiona, Shapely, Geopandas, and Rasterio

Provides a strong foundation for those seeking to learn the basics of Python and apply it to geospatial data analysis

Introduces object-oriented programming concepts in Python, fostering a deeper understanding of Python's capabilities

Emphasizes practical application through Jupyter notebooks, enabling learners to apply their knowledge immediately

Provides a comprehensive introduction to PyQt, a powerful library for creating graphical user interfaces in Python

Covers unit testing, an essential practice for ensuring code quality and reliability

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.

Save

Reviews summary

Foundational python for gis applications

According to students, this course provides a solid introduction to Python for GIS. Learners appreciate its coverage of essential libraries like Geopandas and Rasterio, making it a great starting point for geospatial data analysis. Many highlight the practical approach and hands-on examples as particularly beneficial. However, some point out that while it offers broad coverage, those seeking deep dives into advanced topics might find its survey nature necessitates supplemental resources. Overall, it's praised for equipping learners with foundational skills.

Excellent for beginners, may lack advanced topic depth.

"As a beginner, I found the pace and depth perfect. It didn't overwhelm me but gave me enough to start."

"If you're already familiar with Python or advanced GIS, some sections might feel like a review, but it's great for fundamentals."

"I would have loved more in-depth coverage on advanced geospatial algorithms, but I understand it's a 'survey' course."

Instructor explains complex topics clearly and effectively.

"The instructor's explanations were very clear, making even complex concepts like object-oriented Python easy to grasp."

"I found the lectures well-structured and the demonstrations easy to follow along with."

"The way the instructor broke down the various packages and their interconnections was really helpful."

Focuses on real-world GIS data analysis with Python.

"The hands-on examples using actual geospatial data made the concepts immediately applicable to my work."

"I found the exercises involving Fiona, Shapely, and Geopandas incredibly useful for my daily GIS tasks."

"The course clearly demonstrates how to leverage Python for practical mapping and data manipulation, which is exactly what I needed."

Provides a comprehensive overview of Python for GIS.

"This course was an excellent starting point for me to understand how Python integrates with GIS. It covers so many essential packages."

"I appreciated the broad survey of topics, from basic Python to specialized GIS libraries like Geopandas. It truly is a great overview."

"For someone new to Python in GIS, this course gave me a fantastic foundational understanding of the ecosystem and how different tools fit together."

Some learners reported difficulties with environment setup.

"Setting up the Python environment with all the necessary GIS libraries was a bit of a hurdle initially, requiring some troubleshooting."

"I spent a good amount of time trying to get all the packages installed correctly, which was frustrating at times."

"Could use more detailed, up-to-date instructions for environment setup, as some dependencies were tricky."

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 Survey of python for GIS applications with these activities:

Create a cheat sheet of Python functions and syntax

Show steps

Create a resource that can be used as a quick reference for Python functions and syntax

Browse courses on Python

Show steps

Gather a list of essential Python functions and syntax
Organize the functions and syntax
Create a cheat sheet

Python for Data Analysis

Show steps

This book provides a comprehensive overview of the Python programming language and its applications in data analysis

View Python for Data Analysis on Amazon

Show steps

Read chapters 1-3
Complete the exercises in chapters 1-3
Read chapters 4-6
Complete the exercises in chapters 4-6

Volunteer at a local GIS organization or government agency

Show steps

Gain hands-on experience and apply your skills to real-world projects

Browse courses on GIS

Show steps

Find a local GIS organization or government agency
Contact the organization or agency
Inquire about volunteer opportunities
Attend volunteer training
Volunteer your time

Five other activities

Expand to see all activities and additional details

Show all eight activities

Peer Code Review

Show steps

Refine your coding skills and understanding through peer review

Browse courses on Python

Show steps

Find a peer
Exchange code
Review each other's code
Provide feedback

Complete tutorials from plotly

Show steps

Familiarity with plotting libraries will greatly enhance your ability to visualize data

Browse courses on Plotting

Show steps

Visit the plotly website
Review the tutorials
Complete the interactive tutorials

Build a Web Mapping Application

Show steps

Combine the core concepts of Python data science and geospatial analysis by building a web mapping application

Browse courses on Development

Show steps

Review the Django tutorial
Set up a Django project
Create a model for your data
Create a view for your data
Create a template for your view

Practice coding challenges

Show steps

Improve your coding skills and problem-solving abilities

Browse courses on Python

Show steps

Find a coding challenge website
Select a challenge
Attempt to solve the challenge
Review the solution

Create a data visualization dashboard

Show steps

Develop your skills in data visualization and dashboard creation

Browse courses on Data Visualization

Show steps

Gather a dataset
Clean and prepare the dataset
Create visualizations
Create a dashboard

Career center

Learners who complete Survey of python for GIS applications will develop knowledge and skills that may be useful to these careers:

Geospatial Analyst

Geospatial Analysts use their knowledge of geography and technology to solve problems. This course can help build a foundation in the python packages used for geospatial analysis, including Fiona, Shapely, GeoPandas, and Rasterio. These packages help Geospatial Analysts work with geospatial data and create maps and other visualizations.

See salaries and explore the career path for Geospatial Analyst

GIS Developer

GIS Developers use their programming skills to build and maintain geographic information systems (GIS). This course can help build a foundation in python, a programming language commonly used by GIS Developers. The course also covers GIS packages, including GeoPandas and Rasterio, which help GIS Developers work with geospatial data.

See salaries and explore the career path for GIS Developer

Data Scientist

Data Scientists use their knowledge of data science to solve problems. This course can help build a foundation in python, a programming language commonly used by Data Scientists. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Data Scientists for data analysis and visualization.

See salaries and explore the career path for Data Scientist

GIS Specialist

GIS Specialists use their knowledge of GIS to solve problems. This course can help build a foundation in the python packages used for GIS, including GeoPandas and Rasterio. These packages help GIS Specialists work with geospatial data and create maps and other visualizations.

See salaries and explore the career path for GIS Specialist

Spatial Data Scientist

Spatial Data Scientists use their knowledge of data science and spatial analysis to solve problems. This course can help build a foundation in python, a programming language commonly used by Spatial Data Scientists. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Spatial Data Scientists for data analysis and visualization.

See salaries and explore the career path for Spatial Data Scientist

Machine Learning Engineer

Machine Learning Engineers design, develop, and maintain machine learning models. This course can help build a foundation in python, a programming language commonly used by Machine Learning Engineers. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Machine Learning Engineers for data analysis and visualization.

See salaries and explore the career path for Machine Learning Engineer

Statistician

Statisticians use their knowledge of statistics to solve problems. This course can help build a foundation in python, a programming language commonly used by Statisticians. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Statisticians for data analysis and visualization.

See salaries and explore the career path for Statistician

Data Engineer

Data Engineers design, build, and maintain data pipelines. This course can help build a foundation in python, a programming language commonly used by Data Engineers. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Data Engineers for data analysis and visualization.

See salaries and explore the career path for Data Engineer

Remote Sensing Analyst

Remote Sensing Analysts use their knowledge of remote sensing to solve problems. This course can help build a foundation in the python packages used for remote sensing, including Rasterio. Rasterio helps Remote Sensing Analysts work with raster data and create maps and other visualizations.

See salaries and explore the career path for Remote Sensing Analyst

Business Analyst

Business Analysts use their knowledge of business and data analysis to solve problems. This course can help build a foundation in python, a programming language commonly used by Business Analysts. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Business Analysts for data analysis and visualization.

See salaries and explore the career path for Business Analyst

Operations Research Analyst

Operations Research Analysts use their knowledge of operations research to solve problems. This course can help build a foundation in python, a programming language commonly used by Operations Research Analysts. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Operations Research Analysts for data analysis and visualization.

See salaries and explore the career path for Operations Research Analyst

Financial Analyst

Financial Analysts use their knowledge of finance and data analysis to solve problems. This course can help build a foundation in python, a programming language commonly used by Financial Analysts. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Financial Analysts for data analysis and visualization.

See salaries and explore the career path for Financial Analyst

Data Analyst

Data Analysts help organizations make better decisions by collecting, cleaning, and analyzing data. This course can help build a foundation in python, a programming language commonly used by Data Analysts. The course covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Data Analysts for data analysis and visualization.

See salaries and explore the career path for Data Analyst

Software Engineer

Software Engineers design, develop, and maintain software applications. This course can help build a foundation in python, a programming language commonly used by Software Engineers. The course also covers object-oriented python and unit tests, which are essential for Software Engineers.

See salaries and explore the career path for Software Engineer

Web Developer

Web Developers design, develop, and maintain websites. This course can help build a foundation in python, a programming language commonly used by Web Developers. The course also covers object-oriented python and unit tests, which are essential for Web Developers.

See salaries and explore the career path for Web Developer

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 Survey of python for GIS applications.

Cover image

Cover image

Data Science from Scratch

Save

Provides a comprehensive overview of data science concepts and techniques. It covers data cleaning, feature engineering, model building, and evaluation from scratch.

Data Science from Scratch: First Principles with...

Data Science from Scratch: First Principles with...

Data Science from Scratch: First Principles with...

Cover image

Cover image

Python for Data Analysis

Save

Serves as an introduction to the key principles of data analysis in Python. It provides a conceptual foundation for data exploration, manipulation, and visualization.

Python for Data Analysis: Data Wrangling with...

Python for Data Analysis

Python for Data Analysis: Data Wrangling with...

Cover image

Cover image

Pandas 1.x Cookbook

Save

Offers a collection of recipes and solutions for common data analysis tasks using Pandas. It can serve as a useful reference for applying Pandas techniques covered in this course.

Pandas 1.x Cookbook - Second Edition: Practical...

Pandas 1.x Cookbook: Practical recipes for...

Financial Theory with Python

Save

Even though this book is targeted specifically at data analysis in finance, its coverage of Python basics, data manipulation, and visualization could serve as valuable background for this course.

Financial Theory with Python: A Gentle Introduction

Cover image

Cover image

Learning Geospatial Analysis with Python

Save

Focuses on geospatial analysis and visualization using Python. While not as comprehensive as some of the other books on this list, it can serve as a concise overview of relevant topics.

Learning Geospatial Analysis with Python - Fourth...

Learning Geospatial Analysis with Python:...

Learning Geospatial Analysis With Python: An...

Learning Geospatial Analysis with Python

Cover image

Cover image

Effective Python

Save

Provides best practices and idioms for writing efficient and maintainable Python code. While not specific to GIS applications, it can enhance the quality and readability of code written for this course.

Effective Python: 90 Specific Ways to Write Better...

Effective Python: 59 Specific Ways to Write Better...

Effective Python: 90 Specific Ways to Write Better...

Effective Python: 59 Specific Ways to Write Better...

Share

Help others find this course page by sharing it with your friends and followers:

Copy Link

Similar courses

Here are nine courses similar to Survey of python for GIS applications.

Data-driven Astronomy

Data-driven Astronomy

Python for Data Science, AI & Development

Python for Data Science, AI & Development

Machine Learning Rapid Prototyping with IBM Watson Studio

Machine Learning Rapid Prototyping with IBM Watson Studio

Fundamentals of Scalable Data Science

Fundamentals of Scalable Data Science

The Raspberry Pi Platform and Python Programming for the Raspberry Pi

The Raspberry Pi Platform and Python Programming for the...

Using Python to Access Web Data

Using Python to Access Web Data

Applied Plotting, Charting & Data Representation in Python

Applied Plotting, Charting & Data Representation in Python

Machine Learning Foundations: A Case Study Approach

Machine Learning Foundations: A Case Study Approach

Python for Genomic Data Science

Python for Genomic Data Science

Udemy Buyer Protection & Guarantee

Verified partner policies & purchase protections

Global Marketplace Leader

Free Trial & Audit

Free Lecture Previews

Free preview video lectures available for all courses; optional 7-day free trial on Personal Plan subscriptions (cancel before trial ends to avoid conversion).

Return & Refund Policy

30-Day Money-Back Guarantee

30-day money-back guarantee on all eligible individual course purchases (provided course content has not been substantially consumed or downloaded). Subscription fees are non-refundable once billed.

Buyer Protections

Verified Academic & Industry Partner

Lifetime access to purchased individual courses and future updates, verifiable certificate of completion, and direct student Q&A forums.

Key Purchase Protections

30-day 100% money-back guarantee on course purchases

Lifetime access on web, mobile, and offline

Certificate of completion included with purchase

Direct instructor Q&A and active student community

OpenCourser Verified Partner Policy details last reviewed: 2026-10-22

Rating

4.4

Effort

13.5 total hours

Via

Udemy

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Explores essential geospatial analysis packages for Python, including NumPy, Matplotlib, Pandas, Fiona, Shapely, Geopandas, and Rasterio

Provides a strong foundation for those seeking to learn the basics of Python and apply it to geospatial data analysis

Introduces object-oriented programming concepts in Python, fostering a deeper understanding of Python's capabilities

Emphasizes practical application through Jupyter notebooks, enabling learners to apply their knowledge immediately

Provides a comprehensive introduction to PyQt, a powerful library for creating graphical user interfaces in Python

Covers unit testing, an essential practice for ensuring code quality and reliability

Share this

Share to help others discover this course.

Link

Begin learning today

Enroll now to gain full access to Survey of python for GIS applications.

Enroll now Enroll in this course

Save for later

Add this course to your list. Find it anytime.

Save

Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser