Course Schedule

The courses below are those offered for the term. (To view the course description, class dates & times, touch on accordion tab by the title.)

State-specific Information for Online Programs

Note: Students should be aware of state-specific information for online programs. For more information, please contact an admissions representative.

  • Online Courses

    430.601.81 - Geographic Information Systems (GIS)

    Heather Hicks

    Online 1/22 - 5/5

    In this introductory course, students become familiar with the concepts and gain the experience necessary to appreciate the utility of Geographic Information Systems in decision-making. Topics covered include the fundamentals of data structures, georeferencing, data classification, querying, cartography, and basic spatial data analysis. The course provides an overview of the capabilities of GIS software and applications of GIS. Class time is divided between lectures and GIS exercises that reinforce critical concepts. Students must complete a term project as part of the course. Offered every semester. Elective option for Govt. Analytics students.

    Technology Fee $200.

    430.602.81 - Remote Sensing: Systems and Applications

    Kenneth (Jon) Ranson

    Online 1/22 - 5/5

    This course introduces remote sensing as an important technology to further our understanding of Earth's land, atmospheric, and oceanic processes. Students study remote sensing science, techniques, and satellite technologies to become familiar with the types of information that can be obtained and how this information can be applied in the natural and social sciences. Applications include assessment of land cover and land use, mapping and analysis of natural resources, weather and climate studies, pollution detection and monitoring, disaster monitoring, and identification of oceanographic features. Offered once a year in Spring.

    Technology Fee $200.

    430.603.81 - Geospatial Statistics

    Orhun Aydin

    Online 1/22 - 5/5

    This course introduces theory and practical application of statistical methods in spatial analysis. Statistical fundamentals will be introduced to expose students to descriptive and inferential methods in spatial statistics. Geostatistical fundamentals will also be covered to introduce methods (in particular, kriging) for modelling spatial and spatio-temporal phenomena. This course will provide working knowledge of theory and practice in spatial statistics and Geostatistics, and will serve as a primer to more advanced courses in spatial statistics and machine learning. Theoretical knowledge will be supplemented with real-world use cases through in-class projects and assignments. Throughout the course, students will be exposed to open-source statistics libraries in R, no previous programming knowledge will be assumed. Offered twice a year.

    Technology Fee $200.

    430.604.81 - Spatial Analytics

    Gergana Miller

    Online 1/22 - 5/5

    This course introduces students to using various techniques for solving spatial problems. The course teaches a proven process one can utilize to address common inquiries related to understanding spatial relationships and patterns. Traditional analytical methods such as suitability analysis, network analysis, geostatistical analysis, spatial interpolation, etc. are examined, along with recent data science and analytics methodologies that help us extract knowledge and insights from data. Examples and assignments are drawn from many applications, such as business, urban planning, public safety, public health, transportation and natural sciences. Offered twice a year. Elective option for Govt. Analytics students.

    Technology Fee $200.

    430.606.81 - Programming in GIS

    Paulus Zandbergen

    Online 1/22 - 5/5

    In this course students will learn how to automate workflows and develop tools using Python as a fundamental language for geospatial technology. The course will first cover introductory python basics, then move into geospatial concepts. It will teach students how to automate simple and complex GIS tasks and functionality, thus simplifying workflows and increasing efficiency. Focus will be placed on following proper coding techniques and patterns. The course will introduce students to Python, ArcPy, Python API, Pandas, Numpy, Jupyter, and Markdown to name a few. Offered twice a year. Prerequisites: 430.600 Web GIS

    Technology Fee $200.

    430.610.81 - GIS for Infrastructure Management

    Mark Washington

    Online 1/22 - 5/5

    This course will familiarize students with applications of Geographic Information Systems (GIS) for infrastructure management. Building, utilizing and sharing reliable asset information and integrating enterprise data will be emphasized, in order to help stakeholders make informed decisions and capitalize on efficiencies of using GIS to support various kinds of facilities and infrastructure. Students will have the opportunity to use GIS applications to do project work in support of facility operations, strategic planning, real estate management, architecture design and construction, sustainability, utilities, buildings and interior space management, drones mapping, among others. Samples will be drawn from large university enterprise with multiple campus locations yet applicable to cities and various other settings. Research and spatial analysis will be conducted using recently acquired GIS orthoimagery, LIDAR and planimetric data for the Johns Hopkins' own Homewood campus. Prerequisite: 430.601 Geographic Information Systems.

    Technology Fee $200.

    430.611.81 - Geospatial Ontologies and Semantics

    Dalia Varanka

    Online 1/22 - 5/5

    The development of very large databases requires innovative approaches to data handling to efficiently communicate information meaning to users. The Geospatial Semantics and Ontologies course examines the foundations, design, and use of data structured as linked data, geospatial ontology, knowledge graphs, and related technology. Linked data and knowledge graphs are based on the node-edge-node triple data model to form graphs that can represent information networks. Triple graphs formatted as Resource Description Framework (RDF) can address challenges associated with information management such as inconsistencies within GIS applications, data associations within related enterprises, and information exchange over the Internet. The course begins with some general approaches to semantics and ontology, and basics of information interchange on the Internet. Linked Data in the form of Extensible Markup Language (XML), its extension Geography Markup Language (GML), and other standards for formal semantics such as Well Known Text (WKT) for specifying geographic coordinate geometries, SPARQL and GeoSPARQL query language, and Web Ontology Language (OWL) for automated logical reasoning and data inference are discussed. Subsequent lessons examine semantic system architecture, ontology design, and linked data mapping. No programming is required, but some required technical literacies, such as Java Script Object Notation (JSON) and Scalable Vector Graphics (SVG), are reviewed. Students complete a project in the last few weeks of the semester. The introductory skills offered in this course build a foundation for advanced geospatial Linked Data and Knowledge Graph applications in the future. Offered once a year. Prerequisite: 430.600 Web GIS

    Technology Fee $200.

    430.618.81 - Advanced Python Scripting for GIS

    Andrew Chapkowski

    Online 1/22 - 5/5

    This course focuses on advanced uses of Python as a scripting tool to automate workflows in GIS and create customized applications. This includes the development of script tools, utilizing advanced ArcPy modules, working with third-party modules, implementing Python geoprocessing services, customizing GIS applications, and more advanced Python functionality. Offered once a year. Prerequisites: 430.606 Programming in GIS.

    Technology Fee $200.

    430.625.81 - System Architecture for Enterprise GIS

    Brian Embley

    Online 1/22 - 5/5

    This is a project-based course, which allows students to build an Enterprise GIS implementation. Various enterprise architecture components, such as portals, servers, data stores, web adaptors, load balancers, enterprise databases and big data stores, real time servers, geoanalytics servers, etc. will be examined and implemented in a deployment scenario. Students will first design the enterprise architecture, then implement it. Students will have multiple Amazon EC2 instances configuration available to them at least for part of the semester, in order to practice setting up this enterprise implementation. Topics such as high availability and disaster recovery, enterprise authentication, and administration through scripting, will be applied. Offered once a year. Prerequisites: 430.600 Web GIS.

    Technology Fee $200.

    430.627.81 - Artificial Intelligence and Machine Learning in Geospatial Technology

    Mansour Raad

    Online 1/22 - 5/5

    The transformational impact of artificial intelligence and machine learning in geospatial data science is profound. This course presents a hands-on approach of applying automated modeling and predictive analytics to solve problems. Smart capabilities are powered by machine learning and GeoAI through the use of correlations of pattern detection to build predictive models and classify outcomes for data never seen before. Use cases from various sectors focusing on prediction and optimization, finding patterns and correlations, advanced object detection and automatic feature extraction, are examined. Offered once a year. Prerequisites: 430.606 Programming in GIS. Python programming experience is required.

    Technology Fee $200.

    430.800.81 - Capstone for Geographic Information Systems

    Heather Hicks

    Online 1/22 - 5/5

    The capstone is the culmination of the instruction and training a student receives in the MS in GIS program. In this course, the student selects a mentor, identifies a topic of interest, acquires the relevant data required for the study, develops a data model and/or analysis method, devises the visualization of the data as part of the data interpretation, and summarizes the study in a final report. Students are encouraged to make their presentations at a GIS conference or publish the results of their study in a peer-reviewed GIS publication. Students are responsible for selecting a mentor who may be a JHU faculty member, a qualified and appropriate person from the student's place of work, or any expert with appropriate credentials. Offered every semester. Prerequisite: core course requirements for MS in GIS, at least eight courses taken in the program.

    Technology Fee $200.