Geospatial Analysis Project (Coursera)

Geospatial Analysis Project (Coursera)

In this project-based course, you will design and execute a complete GIS-based analysis – from identifying a concept, question or issue you wish to develop, all the way to final data products and maps that you can add to your portfolio. What you will learn: create a GIS project proposal; develop a hypothesis for a GIS-based question; complete a data analysis in line with your project objectives; interpret and explain the results you obtained in comparison to your original GIS question and/or hypothesis.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Your completed project will demonstrate your mastery of the content in the GIS Specialization and is broken up into four phases:
Milestone 1: Project Proposal - Conceptualize and design your project in the abstract, and write a short proposal that includes the project description, expected data needs, timeline, and how you expect to complete it.
Milestone 2: Workflow Design - Develop the analysis workflow for your project, which will typically involve creating at least one core algorithm for processing your data. The model need not be complex or complicated, but it should allow you to analyze spatial data for a new output or to create a new analytical map of some type.
Milestone 3: Data Analysis – Obtain and preprocess data, run it through your models or other workflows in order to get your rough data products, and begin creating your final map products and/or analysis.
Milestone 4: Web and Print Map Creation – Complete your project by submitting usable and attractive maps and your data and algorithm for peer review and feedback.
Course 5 of 5 in the Geographic Information Systems (GIS) Specialization.

Syllabus

WEEK 1
Course Overview and Milestone 1: Project Proposal
In this milestone, you will have weeks 1 and 2 to build a project proposal that contains your research question or hypothesis, background information, potential data sources and methods, and your expected results. This proposal will lead you into future milestones by providing a guide to help keep your analysis on track. You will start by getting an overview of the entire project and the assignment for this first milestone. From there, you will learn about some sources for project ideas and data sources and look at an example project proposal.

WEEK 2
Milestone 1: Project Proposal Submission
In this module, you will continue to work through Milestone 1, your project proposal as outlined in the first week. You will then submit your proposal for peer review.

WEEK 3
Milestone 2: Planning Your Workflow
In this milestone, you will have week 3 to practice your algorithmic development. In the previous milestone, you posed a question you want to answer - now you'll develop a plan, your algorithm, for how to answer that question with GIS. In practice, this means you'll develop a ModelBuilder model that shows your planned analysis workflow, or some part of it. For those of you who are conducting an analysis that's not conducive to making a model, you can write out your series of steps instead. Regardless, by the end of this module, you'll have a plan for how to produce your results.

WEEK 4
Milestone 3: Data Analysis
For this milestone, you will have weeks 4, 5, and 6 to process your data according to the model you created in the previous milestone, reinforcing your data analysis concepts and practice. When you complete your analysis, you will add metadata to any resulting layers, and you will also write an assessment of what the results mean and how they answer your research question.

WEEK 5
Milestone 3: Data Analysis Continue
In this module, you will continue to work through Milestone 3, analyzing your data as outlined in the fourth week. Pay close attention to data quality issues and your metadata, as reviewed in this week's videos. You will have one more week to complete your data analysis.

WEEK 6
Milestone 3: Data Analysis Submission
In this module, you will continue to work through Milestone 3, analyzing your data as outlined in the fourth and fifth week. You will then submit your data analysis for peer review.

WEEK 7
Milestone 4: Creating Your Maps
In this module, you will have weeks 7 and 8 to hone your map-making skills, building at least two maps that visually interpret the results of your analysis. In making both a web map and a print-layout map, as well as through extra practice materials, you'll refine cartographic techniques that you previously learned as well as new ones to help you to better display information in map form. Should you choose to, you will also build a small website for your project by the time you complete this module.

WEEK 8
Milestone 4: Creating Your Maps Submission
In this module, you will continue to work through Milestone 4, creating your maps as outlined in the seventh week. You will then submit your maps for peer review.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Pre-MBA Statistics (Coursera) Coursera
Indian Institute of Management Ahmedabad (IIMA)

Pre-MBA Statistics (Coursera)

Welcome to the Pre-MBA Statistics course! By the end of this course, you will be able to describe how statistics can be used to summarize, analyze, and interpret data. This course introduces you to some aspects of descriptive and inferential statistics. You will learn to distinguish between various data types and describe the operations that you can execute with each type of data and the right tools to use.

Aug 17th 2026
5-12 Weeks
Analytics in Healthcare Management and Administration (Coursera) Coursera
Northeastern University

Analytics in Healthcare Management and Administration (Coursera)

This course is the continuation of Healthcare Analytics Essentials . If you have not yet taken the Healthcare Analytics Essentials course, it is recommended that you complete that course prior to this course. The foundational knowledge to support the project are carried through in this deeper dive into using healthcare analytics in management and administration.

Aug 17th 2026
4 Weeks
Geographical Information Systems - Part 1 (Coursera) Coursera
École Polytechnique Fédérale de Lausanne

Geographical Information Systems - Part 1 (Coursera)

This course is organized into two parts presenting the theoretical and practical foundations of geographic information systems (GIS). Together theses courses constitute an introduction to GIS and require no prior knowledge. By following this introduction to GIS you will quickly acquire the basic knowledge required to create spatial databases and produce high-quality maps and cartographic representations. This is a practical course and is based on free, open-source software, including QGIS.

Aug 17th 2026
5-12 Weeks
Julia Scientific Programming (Coursera) Coursera
University of Cape Town

Julia Scientific Programming (Coursera)

This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more.

Aug 17th 2026
4 Weeks
Advanced Data Analysis and Collaboration in Qlik Sense (Coursera) Coursera
Coursera Instructor Network

Advanced Data Analysis and Collaboration in Qlik Sense (Coursera)

This course is an advanced level course designed for learners who want to use Qlik Sense to perform sophisticated data analytics, build dashboards, and communicate full reports and stories from their data. These advanced concepts include more than just visualization features such as dynamic filtering and conditional formatting, but more so data functionality such as advanced expressions, drill-downs, leads, lags, and more. This is important as these skills are directly required when creating sophisticated business analyses and dashboards.

Aug 17th 2026
1 Week
Advanced Reproducibility in Cancer Informatics (Coursera) Coursera
Johns Hopkins University

Advanced Reproducibility in Cancer Informatics (Coursera)

This course introduces tools that help enhance reproducibility and replicability in the context of cancer informatics. It uses hands-on exercises to demonstrate in practical terms how to get acquainted with these tools but is by no means meant to be a comprehensive dive into these tools. The course introduces tools and their concepts such as git and GitHub, code review, Docker, and GitHub actions.

Aug 17th 2026
5-12 Weeks
Introduction to PySpark (Coursera) Coursera
Edureka

Introduction to PySpark (Coursera)

Welcome to Introduction to PySpark, a short course strategically crafted to empower you with the skills needed to assess the concepts of Big Data Management and efficiently perform data analysis using PySpark. Throughout this short course, you will acquire the expertise to perform data processing with PySpark, enabling you to efficiently handle large-scale datasets, conduct advanced analytics, and derive valuable insights from diverse data sources.

Aug 17th 2026
1 Week
Big Data Analysis with Scala and Spark (Coursera) Coursera
École Polytechnique Fédérale de Lausanne

Big Data Analysis with Scala and Spark (Coursera)

Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout.

Aug 17th 2026
4 Weeks
Interprofessional Healthcare Informatics (Coursera) Coursera
University of Minnesota

Interprofessional Healthcare Informatics (Coursera)

Interprofessional Healthcare Informatics is a graduate-level, hands-on interactive exploration of real informatics tools and techniques offered by the University of Minnesota and the University of Minnesota's National Center for Interprofessional Practice and Education. We will be incorporating technology-enabled educational innovations to bring the subject matter to life. Over the 10 modules, we will create a vital online learning community and a working healthcare informatics network.

Aug 17th 2026
5-12 Weeks