Geographic Information System (GIS)
Knowledge of Geographic Information Systems (GIS) is an increasingly sought after skill in industries from agriculture to public health. This Specialization, offered in partnership with ArcGIS developer Esri, will teach the skills you need to successfully use GIS software in a professional setting. You will learn how to analyze your spatial data, use cartography techniques to communicate your results in maps, and collaborate with peers in GIS and GIS-dependent fields. In the final Capstone Project, you will create a professional-quality GIS portfolio piece using a combination of data identification and collection, analytical map development, and spatial analysis techniques.
Fundamentals of GIS
Explore the world of spatial analysis and cartography with geographic information systems (GIS). 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.
GIS Data Formats, Design and Quality
In this course, the second in the Geographic Information Systems (GIS) Specialization, you will go in-depth with common data types (such as raster and vector data), structures, quality and storage during four week-long modules: Week 1: Learn about data models and formats, including a full understanding of vector data and raster concepts. You will also learn about the implications of a data’s scale and how to load layers from web services. Week 2: Create a vector data model by using vector attribute tables, writing query strings, defining queries, and adding and calculating fields. You'll also learn how to create new data through the process of digitizing and you'll use the built-in Editor tools in ArcGIS. Week 3: Learn about common data storage mechanisms within GIS, including geodatabases and shapefiles. Learn how to choose between them for your projects and how to optimize them for speed and size. You'll also work with rasters for the first time, using digital elevation models and creating slope and distance analysis products. Week 4: Explore datasets and assess them for quality and uncertainty. You will also learn how to bring your maps and data to the Internet and create web maps quickly with ArcGIS Online. Take GIS Data Formats, Design and Quality as a standalone course or as part of the Geographic Information Systems (GIS) Specialization. You should have equivalent experience to completing the first course in this specialization, Fundamentals of GIS, before taking this course. By completing the second class in the Specialization you will gain the skills needed to succeed in the full program.
Geospatial and Environmental Analysis
Apply your GIS knowledge in this course on geospatial analysis, focusing on analysis tools, 3D data, working with rasters, projections, and environment variables. Through all four weeks of this course, we'll work through a project together - something unique to this course - from project conception, through data retrieval, initial data management and processing, and finally to our analysis products. In this class you will learn the fundamentals of geospatial and environmental analysis during four week-long modules: Week 1: Tour ArcToolbox and learn how to use common geospatial analysis tools built into ArcGIS Week 2: Gain a working understanding of raster data models: symbolize, reproject, overlay, and assess rasters. Take a detour into 3D data models, and interpolation of observations into 3D surfaces and rasters Week 3: Go in-depth on projections and coordinate systems, which are foundational to all GIS. Learn how to use environment variables to constrain your analyses and get better quality data products. Week 4: Expand your knowledge of symbology. Learn how to visually display your data by classifying it in logical groupings and then symbolizing it on your map. Take Geospatial and Environmental Analysis as a standalone course or as part of the Geographic Information Systems (GIS) Specialization. You should have equivalent experience to completing the first and second courses in this specialization, "Fundamentals of GIS" and "GIS Data Formats, Design, and Quality", before taking this course. By completing this third class in the Specialization you will gain the skills needed to succeed in the full program.
Imagery, Automation, and Applications
Welcome to the last course of the specialization (unless your continuing on to the capstone project, of course!). Using the knowledge you’ve learned about ArcGIS, complete technical tasks such raster calculations and suitability analysis. In this class you will become comfortable with spatial analysis and applications within GIS during four week-long modules: Week 1: You'll learn all about remotely sensed and satellite imagery, and be introduced to the electromagnetic spectrum. At the end of this week, you'll be able to find and download satellite imagery online and use it for two common types of analysis: NDVI and trained classification. Week 2: You'll learn how to use ModelBuilder to create large processing workflows that use parameters, preconditions, variables, and a new set of tools. We'll also explore a few topics that we don't really have time to discuss in detail, but might whet your appetite for future learning in other avenues: geocoding, time-enabled data, spatial statistics, and ArcGIS Pro. Week 3: In week three, we'll make and use digital elevation models using some new, specific tools such as the cut fill tool, hillshades, viewsheds and more. We'll also go through a few common algorithms including a very important one: the suitability analysis. Week 4: We'll begin the final week by talking about a few spatial analyst tools we haven't yet touched on in the specialization: Region Group to make our own zones, Focal Statistics to smooth a hillshade, Reclassify to change values, and Point Density to create a density surface. Finally, we'll wrap up by talking about a few more things that you might want to explore more as you start working on learning about GIS topics on your own. Take Geospatial and Environmental Analysis as a standalone course or as part of the Geographic Information Systems (GIS) Specialization. You should have equivalent experience to completing the first, second, and third courses in this specialization, "Fundamentals of GIS," "GIS Data Formats, Design, and Quality", and "Geospatial and Environmental Analysis," respectively, before taking this course. By completing the fourth class you will gain the skills needed to succeed in the Specialization capstone.
Geospatial Analysis Project
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. 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.