Fundamentals of GIS (Coursera)

Fundamentals of GIS (Coursera)

Explore the world of spatial analysis and cartography with geographic information systems (GIS). What you will learn: define core geospatial concepts; practice with subset data using selections and feature attributes; create map books using advanced mapping techniques; create layer and map packages.

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

In this class you will learn the basics of the industry’s leading software tool, ArcGIS, during four week-long modules:
Week 1: Learn how GIS grew from paper maps to the globally integrated electronic software packages of today. You will install ArcGIS on your computer and learn how to use online help to answer technical questions.
Week 2: Open up ArcGIS and explore data using ArcMap. Learn the foundational concepts of GIS, how to analyze data, and make your first map.
Week 3: Make your own maps! Symbolize data and create an eye-catching final product.
Week 4: Share your data and maps and learn to store and organize your data.
Take Fundamentals of GIS as a standalone course or as part of the Geographic Information Systems (GIS) Specialization. By completing the first class in the Specialization you will gain the skills needed to succeed in the full program.
Students who need an ArcGIS license will receive a non-commercial, 1 year student license for participation in this course and specialization.
Course 1 of 5 in the Geographic Information Systems (GIS) Specialization.

Syllabus

WEEK 1
Course Introduction and Introduction to Geographic Information Systems (GIS)
In this module, we will cover course expectations, give you a quick overview of GIS and what's great about it, take a first look at ArcGIS and identify key elements in the interface, and define core geospatial concepts and terminology. In Section 2, we will discuss options for desktop GIS, the history of GIS and how it's used today, discuss resources and help that you can use, and lay out core skills that are relevant to you as a GIS analyst. We'll close out by showing you how to get a copy of ArcGIS for this course, and with a tutorial on getting started in ArcGIS.

WEEK 2
ArcGIS Basics
In this module, we will explore GIS data using ArcMap and will explore and change properties of GIS layers to change map displays. We will subset data using selections, and explore feature attributes. Finally, we will learn about projections and use that knowledge as we run geoprocessing tools.

WEEK 3
Making Maps With Common Datasets
In this module we will identify common datasets in both the US and Internationally. We will use a new mode in ArcGIS to create complete maps that include proper symbology, legends, titles, north arrows, and data sources. We will further use more advanced mapping techniques to output map books and label items on the map.

WEEK 4
Retrieving and Sharing Data
In this module, we will view and edit metadata in order to create higher quality data. We will retrieve data from the web and share data, discuss workspaces and file formats, and create layer and map packages. We will also use multiple file formats for GIS data and be able to appropriately choose between them based upon project requirements.

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

Related Courses

Dealing With Missing Data (Coursera) Coursera
University of Maryland, College Park

Dealing With Missing Data (Coursera)

This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For both weighting and imputation, the capabilities of different statistical software packages will be covered, including R®, Stata®, and SAS®.

Jun 29th 2026
4 Weeks
Regression Modeling in Practice (Coursera) Coursera
Wesleyan University

Regression Modeling in Practice (Coursera)

This course focuses on one of the most important tools in your data analysis arsenal: regression analysis. Using either SAS or Python, you will begin with linear regression and then learn how to adapt when two variables do not present a clear linear relationship. You will examine multiple predictors of your outcome and be able to identify confounding variables, which can tell a more compelling story about your results. You will learn the assumptions underlying regression analysis, how to interpret regression coefficients, and how to use regression diagnostic plots and other tools to evaluate the quality of your regression model. Throughout the course, you will share with others the regression models you have developed and the stories they tell you.

Jul 3rd 2026
4 Weeks
Data Science Companion (Coursera) Coursera
MathWorks

Data Science Companion (Coursera)

The Data Science Companion provides an introduction to data science. You will gain a quick background in data science and core machine learning concepts, such as regression and classification. You’ll be introduced to the practical knowledge of data processing and visualization using low-code solutions, as well as an overview of the ways to integrate multiple tools effectively to solve data science problems.

Jul 3rd 2026
4 Weeks
GIS Data Formats, Design and Quality (Coursera) Coursera
University of California, Davis

GIS Data Formats, Design and Quality (Coursera)

In this course, the second in the Geographic Information Systems (GIS) Specialization. What you will learn: design data tables and use separating and joining data in a relational database; write query strings to subset data; create and work with raster data; create web maps.

Jun 29th 2026
4 Weeks
Case studies in business analytics with ACCENTURE (Coursera) Coursera
ESSEC Business School

Case studies in business analytics with ACCENTURE (Coursera)

This course is RESTRICTED TO LEARNERS ENROLLED IN Strategic Business Analytics SPECIALIZATION as a preparation to the capstone project. During the first two MOOCs, we focused on specific techniques for specific applications. Instead, with this third MOOC, we provide you with different examples to open your mind to different applications from different industries and sectors. The objective is to give you an helicopter overview on what's happening in this field. You will see how the tools presented in the two previous courses of the Specialization are used in real life projects.

Jun 29th 2026
3 Weeks
Business Metrics for Data-Driven Companies (Coursera) Coursera
Duke University

Business Metrics for Data-Driven Companies (Coursera)

In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs.

Jun 29th 2026
4 Weeks
Managing Data Analysis (Coursera) Coursera
Johns Hopkins University

Managing Data Analysis (Coursera)

This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results.

Jun 29th 2026
1 Week
Ask Questions to Make Data-Driven Decisions (Coursera) Coursera
Google

Ask Questions to Make Data-Driven Decisions (Coursera)

This is the second course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. You’ll build on your understanding of the topics that were introduced in the first Google Data Analytics Certificate course. The material will help you learn how to ask effective questions to make data-driven decisions, while connecting with stakeholders’ needs. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Jun 30th 2026
4 Weeks
Share Data Through the Art of Visualization (Coursera) Coursera
Google

Share Data Through the Art of Visualization (Coursera)

This is the sixth course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. You’ll learn how to visualize and present your data findings as you complete the data analysis process. This course will show you how data visualizations, such as visual dashboards, can help bring your data to life. You’ll also explore Tableau, a data visualization platform that will help you create effective visualizations for your presentations.

Jun 30th 2026
4 Weeks
The Data Scientist's Toolbox (Coursera) Coursera
Johns Hopkins University

The Data Scientist's Toolbox (Coursera)

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

Jun 29th 2026
4 Weeks
Data Visualization and Communication with Tableau (Coursera) Coursera
Duke University

Data Visualization and Communication with Tableau (Coursera)

One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand. In this course you will learn how to become a master at communicating business-relevant implications of data analyses.

Jun 29th 2026
5-12 Weeks
Introduction to Big Data (Coursera) Coursera
University of California, San Diego

Introduction to Big Data (Coursera)

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world!

Jun 29th 2026
3 Weeks